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Journal of Medical Internet Research
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Design Guidelines for Online Health Forums: User-Centered Design Approach
Background: Online health forums are used widely, yet evidence of their effectiveness is inconsistent. Evidence-based forum design guidance grounded in theory and lived experience could improve the efficacy and outcomes of these forums for the many people using them worldwide. Objective: This study aimed to draw on the experience of online forum users and staff, and insights from existing research on technology design and self-determination theory, to generate a set of theoretically grounded gui
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Journal of Medical Internet Research
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Evaluation of the Square Eyes Model as a Screening Tool for Identifying Digital Technologies in Wearable Camera Images Among Children: Laboratory Study
Background: Accurate measurements of children’s digital technology use are essential for understanding its potential implications on health and well-being. Wearable cameras can provide such measurements, but image coding is a high burden for researchers. Machine learning–based object-recognition models have the potential to reduce this burden by identifying images containing technology. Objective: This study aims to evaluate the performance of an object recognition model, the Square Eyes model,
Evaluation of the Square Eyes Model as a Screening Tool for Identifying Digital Technologies in Wearable Camera Images Among Children: Laboratory Study
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MIT Technology Review
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Donated livers can be made biologically younger
Once an organ is removed from a donor’s body, the clock starts ticking. Surgeons usually flush the organ with a preservative solution, bag it, and put it on ice—where it immediately starts to degrade. The team has a matter of hours to get it into a recipient’s body. There’s another option—one that has been growing in popularity in recent years, especially for donated organs that aren’t in the healthiest state. Some hospitals opt to put them on machines that pump them with nutrients and rem
Donated livers can be made biologically younger
Once an organ is removed from a donor’s body, the clock starts ticking. Surgeons usually flush the organ with a preservative solution, bag it, and put it on ice—where it immediately starts to degrade. The team has a matter of hours to get it into a recipient’s body.
There’s another option—one that has been growing in popularity in recent years, especially for donated organs that aren’t in the healthiest state. Some hospitals opt to put them on machines that pump them with nutrients and remove waste products, usually for around six to 12 hours. It’s a bit like being back in a body.
This allows doctors to assess the organs, and some recent studies suggest that time spent on these perfusion machines helps them do better once they’re transplanted. Now, scientists have found that perfused organs seem to get younger, at least at a molecular level.
The research, shared with MIT Technology Review, provides molecular clues as to why organs from younger donors are known to have a higher success rate. It might also help explain why perfused organs are less likely to fail once they make it into a recipient.
The researchers behind the study hope to find new ways to test the health of donated organs and potentially develop additional tools to repair organs that might otherwise be discarded. “If [we] can improve the utilization of organs beyond what the current systems can do, then that’s a win in my book,” says Jesse Poganik, who studies aging at Brigham and Women’s Hospital in Boston and coauthored the study.
Clocking organs
Poganik—along with colleagues including Heidi Yeh and Alban Longchamp, transplant surgeons at Mass General Brigham—used “aging clocks” to assess donated livers. These are scientific tools designed to measure biological age—a result that is meant to convey more about the health status of an organ (or person) than chronological age.
In an initial experiment, the team used a clock to look at the patterns of chemical marks on DNA in 37 samples taken from 19 donated livers. Such epigenetic patterns are known to change as we age. But when the team compared samples from livers kept on ice and those that were perfused, the team found a “striking” pattern in the latter.
“Machine-perfused livers, in spite of being older or having other disadvantageous characteristics, had a biological age that was lower than [non-perfused] livers that were chronologically younger,” says Yeh, who led the work.
To investigate further, Yeh and her colleagues analyzed another 208 samples from 103 donated livers. This time, they used different aging clocks—ones that essentially measure how genes are working. They studied samples biopsied from the livers after they had been stored for up to around six hours either in cold storage or on machine perfusion.
In most cases, they also assessed a second sample taken around an hour after the livers had been transplanted into a recipient. Once the organ’s blood supply is reestablished in the body, “you have a few other things to do,” says Longchamp. “Then you just do a quick biopsy before you close.”
According to the clocks, which were developed to measure age and risk of death, the machine-perfused livers were biologically younger, the team found. “Pumping them at 34 degrees with oxygen and nutrients actually reversed the biological age,” says Longchamp. The results have been been shared with colleagues at an industry conference, he says.
“If you adjust out chronological age … to have a fair head-to-head comparison, the difference between the two is on the order of 30%,” says Poganik. “It’s logical to say that perfusion drives this effect.”
The biological ages of all the livers tended to increase as soon as they were put into a recipient’s body, probably as a result of stresses on the organs. But still, the effect endured—the perfused organs remained biologically younger.
Nathanael Raschzok, a transplant surgeon at Charité Universitätsmedizin Berlin in Germany who was not involved in the research, says the work is impressive. But it’s not yet clear what these changes might mean for the recipients of these organs, he says. The organs in the study were donated by people in their 30s, 40s, and 50s. Raschzok wants to know the effect of perfusion on the liver of an 80-year-old. “Every so often, we use organs from 70-, 80-, 85-year-old donors,” he says.
A better understanding of why the organs appear to be getting biologically younger might lead to therapies that achieve the same effect with a drug that could potentially be used to treat a donated organ for a fraction of the price, he adds. That’s important because perfusion is expensive—Raschzok says it costs around €10,000 in Germany (a quarter of the budget for a transplant), while the cost in the US comes to around $80,000 to $100,000 per organ, says Yeh.
Molecular repair
Yeh and her colleagues weren’t able to study most of the livers before perfusion. That’s because donated organs are generally not considered to be under the purview of the hospital until they’ve been placed on perfusion machines, she says. (Organ procurement procedures vary, but for the team as Mass General Brigham, donated organs are put on perfusion devices at the donor’s hospital. “There’s this sort of nebulous period where it’s not clear who the organ belongs to,” says Yeh.)
Still, by looking at the genes and molecular pathways that seem to be altered in perfused organs, she and her colleagues can garner some clues. At a molecular level, the team saw changes in cell pathways linked to inflammation and the structure of tissues, for example. They also saw more activity in a pathway that allows cells to remove and recycle damaged cell parts, says Yeh.
Poganik hopes to develop some kind of test that would determine which organs, on the basis of their biological age, are suitable for transplantation. He and his colleagues are also experimenting with potential drug treatments that might push the biological age of an organ even lower.
In the meantime, any liver that is not from a “perfect, young, brain-dead donor” could probably benefit from perfusion, says Yeh. The devices are already transforming transplant surgery. Just a few years ago, she says, she and her colleagues would avoid using livers from people who’d suffered a circulatory death (when the heart stops beating and there’s a damaging lack of blood flow to organs) and were over 40. Today, they use livers from such donors over the age of 70. “Perfusion has completely changed the landscape of transplantation in the last three years,” she says.
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MIT Technology Review

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The Download: AI’s real extinction threat and age-reversal tech for eyes
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Roundtables: could AI really kill us all? Employees at the world’s leading AI labs are saying there’s a real possibility that advanced AI could destroy humanity. Are they right? Or is this more scaremongering and hype? Join MIT Technology Review executive editor Niall Firth, senior AI editor Will Douglas Heaven, and AI reporter Grace Huckins for a sub
The Download: AI’s real extinction threat and age-reversal tech for eyes
This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology.
Roundtables: could AI really kill us all?
Employees at the world’s leading AI labs are saying there’s a real possibility that advanced AI could destroy humanity. Are they right? Or is this more scaremongering and hype?
Join MIT Technology Review executive editor Niall Firth, senior AI editor Will Douglas Heaven, and AI reporter Grace Huckins for a subscriber-only conversation unpacking the debate around AI extinction. They’ll explore where the fears come from, whether they hold any water and, if they do, what we should do about them.
Register now to attend on Tuesday, September 15 at 16:00 BST / 11:00am EST / 8:00am PST.
Want to join the conversation? Subscribe to MIT Technology Review for exclusive access to all our Roundtables.
This geneticist’s age-reversal tech could help restore sight
Yuancheng (Ryan) Lu is obsessed with aging. And with eyes. As he steps outside the Whitehead Institute in Cambridge, Massachusetts, his aviator glasses darken automatically in the sun. Age-related blindness runs in his family, and his own 23andMe test came back with a mutation for macular degeneration, a top cause of vision loss in old age.
That obsession extends to his work. Lu is behind one of the coolest results in rejuvenation science and eye research: an age-reversal technique called reprogramming that repaired the optic nerves of blind mice, restoring their vision. Now, nearly the same genetic therapy he developed as a student has entered human clinical trials.
Learn more about Lu’s work on restoring sight with age-reversal therapy.
—Antonio Regalado
Yuancheng (Ryan) Lu is one of the biotechnology and health honorees on our 35 Innovators Under 35 list for 2026. Meet the rest of them here, or explore the full list across the biotechnology and health, AI, computing and robotics, and climate and energy categories.
The must-reads
I’ve combed the internet to find you today’s most fun/important/scary/fascinating stories about technology.
1 Dario Amodei, Sam Altman, and Elon Musk have called for an AI slowdown
In a rare show of unity, the rivals agreed that AI needs stronger brakes. (Guardian)
+ Amodei wants independent monitors and new industry-wide rules. (BBC)
+ Altman called for pacing, but not stopping. (Bloomberg $)
+ While Musk said on X that “Dario is right.”(WSJ $)
+ AI-linked stocks slumped in response. (FT $)
+ Chinese state media blasted the calls as a “Cold War” tactic. (Reuters $)
+ AI’s impacts are getting harder to predict. (MIT Technology Review)
2 Trump and Congress are resisting calls for stronger AI regulation
Trump downplayed AI risks, prioritizing the AI race with China. (NPR)
+ While the House Speaker said Congress won’t lead on AI regulation. (Politico $)
+ But Democrats are pushing for new rules before the midterms. (CNBC)
+ States and the White House are dividing over AI. (MIT Technology Review)
3 China plans to lead AI development across the BRICS countries
President Xi proposed open-source AI cooperation. (CNBC)
+ Beijing’s spy agency has warned of AI threats to national security. (FT $)
4 South Korea has tightened espionage laws to protect its chip secrets
Foreign spies can now face up to 30 years in prison. (FT $)
+ The changes follow alleged transfers of Samsung tech to China. (Reuters $)
5 The US and Mexico are teaming up to zap drones at the border
The operation may employ high-energy lasers.(Wired $)
+ Ukraine is a Wild West market for drone data. (MIT Technology Review)
6 AI agents are creating a new problem for the criminal justice system
The law has no clear answer when AI agents act independently. (Bloomberg $)
+ While courts face a flood of AI-generated lawsuits. (MIT Technology Review)
7 A Waymo pulled over and alerted police after detecting a gun
The riders were juveniles carrying a loaded AR-style ghost gun. (LA Times $)
8 Meta has been sued over data used to train its smart glasses
It allegedly used Facebook and Instagram photos without consent. (Wired $)
9 A hidden crypto farm in Mexico has put a spotlight on cartel funding
Authorities are investigating whether it stole power from a nearby dam. (Reuters $)
10 StarCraft is returning in 2030 as an open-world shooter
Fifteen years since its last release, the iconic franchise will be reborn. (Verge)
Quote of the day
“Dr. Frankenstein is telling us the monster is escaping; help us stop this.”
—Sen. Ruben Gallego, D-Ariz, calls for new AI regulation on CNN’s “State of the Union.”
One more thing

Inside the hunt for the most dangerous asteroid ever
As asteroid 2024 YR4 hurtled toward Earth, astronomers determined that this massive rock posed a higher risk of impact than any object of its size in recorded history. Then, just as quickly as history was made, experts declared that the danger had passed.
This is the inside story of the network of global scientists who found, followed, planned for, and finally dismissed the most dangerous asteroid ever found—all under the tightest of timelines and with the highest of stakes. Find out how they did it.
—Robin George Andrews
We can still have nice things
A place for comfort, fun, and distraction to brighten up your day. (Got any ideas? Drop me a line.)
+ This master paperboy delivers newspapers with astonishing speed and skill.
+ Public Enemy and Led Zeppelin collide in this gloriously unlikely musical mashup.
+ Dozens of synchronized lasers have created extraordinary kaleidoscopic starburst patterns.
+ Check out the breathtaking winning images from the 2026 International Aerial Photographer of the Year competition.
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cs.AI, q-bio.NC updates on arXiv.org
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Reading the Whole Heart: Latent-Attention Masked Autoencoders for Multimodal Cardiac Representation Learning
arXiv:2609.12035v1 Announce Type: new Abstract: Cardiovascular diagnosis rests on integrating complementary modalities, like ECG, echocardiography, chest radiographs, and clinical variables, each capturing distinct but correlated aspects of cardiac physiology. Yet most medical foundation models remain modality-specific, combining modalities only for finetuning or post-training. This discards the cross-modal evidence clinicians naturally integrate and ignores the structure within each modality.
Reading the Whole Heart: Latent-Attention Masked Autoencoders for Multimodal Cardiac Representation Learning
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cs.AI, q-bio.NC updates on arXiv.org
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Soft Symbol Grounding for Prototypical Concepts
arXiv:2609.12247v1 Announce Type: new Abstract: Neuro-symbolic models are usually trained with supervision only on final labels, leaving the intermediate concepts unobserved. Since many concept assignments are consistent with a given label, training can predict labels correctly while recovering the wrong concepts, a failure known as a reasoning shortcut. Prototypical networks reduce shortcuts by anchoring each concept to a few labeled examples, but existing methods still couple perception and r
Soft Symbol Grounding for Prototypical Concepts
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cs.AI, q-bio.NC updates on arXiv.org
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AIM: A Privacy-Aware Interoperable Memory Framework for Multi-Agent Multi-User LLM Systems
arXiv:2609.12320v1 Announce Type: new Abstract: Traditional large language models (LLMs) are scoped to individual user sessions, limiting their knowledge to a single conversation and preventing them from learning user preferences that evolve over time. Existing agentic memory systems address this limitation but generally operate at the individual-user level, restricting the public knowledge that could be shared across users to improve downstream responses. We introduce AIM (Agentic Interoperabl
AIM: A Privacy-Aware Interoperable Memory Framework for Multi-Agent Multi-User LLM Systems
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cs.AI, q-bio.NC updates on arXiv.org
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BlueLM-GUI Technical Report: A Real-Device-Centric Flywheel for Self-Improving Mobile GUI Agents
arXiv:2609.12394v1 Announce Type: new Abstract: Mobile GUI agents are shifting from multi-module frameworks to native models trained end-to-end, yet industrial deployment faces three persistent gaps. Sandbox training produces a distribution mismatch with production environments; expensive real-device failures remain underutilized; and fixed benchmarks saturate, losing the power to guide iteration. We present BlueLM-GUI, a 35B-A3B mobile GUI agent built as a real-device-centric flywheel that clo
BlueLM-GUI Technical Report: A Real-Device-Centric Flywheel for Self-Improving Mobile GUI Agents
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cs.AI, q-bio.NC updates on arXiv.org
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Is Gaussian Splatting Becoming Neural Again? A Taxonomy and Controlled Study of Learned Parameterization
arXiv:2609.12395v1 Announce Type: new Abstract: Three-dimensional Gaussian Splatting (3DGS) combines explicit primitives with efficient rasterization, yet recent systems increasingly use neural networks to generate or share Gaussian parameters. We characterize this trend along five axes: attribute decoding, spatial sharing, view-conditioned decoding, topology generation, and amortized inference. An analysis of 19 representative methods shows that these choices address different limitations and
Is Gaussian Splatting Becoming Neural Again? A Taxonomy and Controlled Study of Learned Parameterization
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cs.AI, q-bio.NC updates on arXiv.org
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When Does AI Augment Work? A Workflow-Level Framework for Human-Agent Collaboration
arXiv:2609.12482v1 Announce Type: new Abstract: We aim to characterise the value of artificial intelligence in the workplace. Current studies largely measure this value in terms of the current automation capabilities and public adoption of AI. However, such metrics ignore the greater impacts of human--agent collaboration in transforming the nature of work. To account for this, we must expand the scope of our analysis beyond atomised tasks of today, and instead focus on how AI can augment entire
When Does AI Augment Work? A Workflow-Level Framework for Human-Agent Collaboration
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cs.AI, q-bio.NC updates on arXiv.org
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Information Specialization and Constrained Synthesis in Multi-Agent LLM Forecasting: A Prospective Live-Study of the 2026 FIFA World Cup
arXiv:2609.12495v1 Announce Type: new Abstract: Large language models are being organized into multi-agent systems with specialized roles, but whether such specialization produces distinct forecasts and whether subsequent synthesis improves utility remains unclear. In this study, we carried out a live, prospective evaluation over the final 56 matches of the information-dense 2026 FIFA World Cup, keeping a frontier foundation model constant while assigning two primary forecasting agents contrast
Information Specialization and Constrained Synthesis in Multi-Agent LLM Forecasting: A Prospective Live-Study of the 2026 FIFA World Cup
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cs.AI, q-bio.NC updates on arXiv.org
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Beyond Generation and Accuracy: Diagnosing and Enhancing Visual Chain-of-Thought for Geometry Problem Solving
arXiv:2609.12606v1 Announce Type: new Abstract: While multimodal reasoning has advanced rapidly, solving complex geometry problems critically hinges on active visual assistance, such as constructing auxiliary lines, spurring the rise of Visual Chain-of-Thought (VCoT). However, existing evaluations typically assess visual generation quality and final answer accuracy in isolation, failing to examine whether intermediate visual aids are geometrically valid, effectively utilized in subsequent reaso
Beyond Generation and Accuracy: Diagnosing and Enhancing Visual Chain-of-Thought for Geometry Problem Solving
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cs.AI, q-bio.NC updates on arXiv.org
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SteerDuplex: Steerable Duplex Speech Dialogue Models
arXiv:2609.12623v1 Announce Type: new Abstract: Full-duplex spoken dialogue models support low-latency turn taking, interruption handling, and backchanneling, yet a key capability remains underexplored: steerability, the ability to reliably shift conversational behavior along attributes such as tone, persona, speaking rate, and voice style in response to user instructions. We introduce a taxonomy of text- and audio-based steerability that identifies substantial gaps in current full-duplex model
SteerDuplex: Steerable Duplex Speech Dialogue Models
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cs.AI, q-bio.NC updates on arXiv.org
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Tracing and Coordinating Cross-Layer Influence for Multimodal Model Merging
arXiv:2609.12897v1 Announce Type: new Abstract: Multimodal model merging aims to consolidate task experts into a single model that retains their complementary capabilities. Most unimodal model merging methods combine expert updates within individual layers, and multimodal approaches largely follow this design. However, an expert update changes the representations passed to subsequent layers, allowing its influence to propagate across depth and affect how visual and textual information interact.
Tracing and Coordinating Cross-Layer Influence for Multimodal Model Merging
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cs.AI, q-bio.NC updates on arXiv.org
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How Good Are Frontier Models at Physics? Expert Re-Grading Reveals Broken Evaluations and Near-Saturation of Leading Benchmarks
arXiv:2609.13009v1 Announce Type: new Abstract: Low reported scores on leading physics benchmarks, including those featured in the Artificial Analysis Intelligence Index (2026), suggest that frontier language models still struggle with advanced physics, a demanding test of their scientific reasoning and quantitative problem-solving abilities. Yet this impression does not always align with domain experts' experiences using these models in their work. We revisit these reported findings by evaluat
How Good Are Frontier Models at Physics? Expert Re-Grading Reveals Broken Evaluations and Near-Saturation of Leading Benchmarks
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cs.AI, q-bio.NC updates on arXiv.org
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SoulAuth: An Actor-native Identity Architecture and Rust Reference Implementation for Humans and Long-lived AI Actors
arXiv:2609.11258v1 Announce Type: cross Abstract: As AI systems move from transient model invocations toward long-lived actors that persist across credentials, clients, sessions, and runtime instances, identity infrastructure must answer a basic question: where should the canonical continuity boundary be placed? This paper introduces Actor-native Identity and presents SoulAuth, an open-source Rust reference implementation for Humans and long-lived AIActors. We argue that any subject that must p
SoulAuth: An Actor-native Identity Architecture and Rust Reference Implementation for Humans and Long-lived AI Actors
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cs.AI, q-bio.NC updates on arXiv.org
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Reality Is the Final Verifier: On Two Key Gaps in Agentic Software Engineering
arXiv:2609.12039v1 Announce Type: cross Abstract: Software development follows an implementation-verification loop in which developers or agents iteratively revise an implementation until an evaluator, such as a test suite, accepts it. The evaluator checks the implementation against a set of requirements under a model of the deployment environment. Yet even a formal proof that the implementation satisfies the requirements under the model cannot guarantee acceptable behavior after deployment. Re
Reality Is the Final Verifier: On Two Key Gaps in Agentic Software Engineering
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cs.AI, q-bio.NC updates on arXiv.org
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Extracting Dataset Mentions in Forced Displacement and FCV Documents: A Weakly Supervised Framework with LLM-Based Label Refinement
arXiv:2609.12107v1 Announce Type: cross Abstract: Development and humanitarian organizations produce and support surveys, administrative registries, and other data resources to inform research, policy, and operations, yet systematically identifying where these datasets are referenced remains difficult. Such references are dispersed across research papers, project documents, humanitarian reports, and other unstructured text, limiting both the ability to trace data use and to identify potential g
Extracting Dataset Mentions in Forced Displacement and FCV Documents: A Weakly Supervised Framework with LLM-Based Label Refinement
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cs.AI, q-bio.NC updates on arXiv.org
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DriftSE: Speech Enhancement with Generative Drifting
arXiv:2609.12252v1 Announce Type: cross Abstract: We propose DriftSE, a novel one-step generative framework for speech enhancement formulated as a latent distribution equilibrium problem. During training, the drifting field aligns the generator's pushforward distribution with the clean speech manifold through drifting in a latent domain. During inference, the drifting process is discarded, enabling one-step generation. We establish that its enhancement quality depends fundamentally on the choic
DriftSE: Speech Enhancement with Generative Drifting
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cs.AI, q-bio.NC updates on arXiv.org
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ESTS at WMT26: Routing-Informed Expert Pruning for Model Compression
arXiv:2609.12310v1 Announce Type: cross Abstract: We describe six submissions under the team name ESTS to the unconstrained WMT26 Model Compression Shared Task for English--Simplified Chinese and English--Egyptian Arabic. We submit three compression operating points per translation direction, all derived from GPT-OSS-20B. We use task-specific routing mass to rank experts and cross-lingual routing divergence to allocate retained capacity across layers, then physically remove low-importance exper