Knowledge catalogue
arXiv:2505.16025v3 Announce Type: replace Abstract: Video quality assessment (VQA) is a challenging research topic with broad applications. Traditional hand-crafted and discriminative learning-based V
arXiv:2605.02123v1 Announce Type: cross Abstract: The increasing use of token-based representations in language-driven applications has motivated wireless token communication, where tokens are treated
arXiv:2603.00822v2 Announce Type: replace-cross Abstract: As Large Language Model (LLM) agents increasingly execute complex, autonomous software engineering tasks, developers rely on natural language
Continuous-video agents (computer use, robotics, static scenes) burn compute re-ingesting pixels that didn't move. VLMaxxing teaches a frozen video VLM to skip the reruns. 54 fps perception on Gemma 4
arXiv:2605.03297v1 Announce Type: cross Abstract: ASR systems based on self-supervised acoustic pretraining and CTC fine-tuning achieve strong performance on native speech but remain sensitive to acce
arXiv:2605.02395v1 Announce Type: new Abstract: Process reward models (PRMs) rely on high-quality process supervision data, yet existing construction methods often provide limited control over error l
arXiv:2605.02033v1 Announce Type: cross Abstract: Conventional commits provide a structured format for writing commit messages, which improves readability, software maintenance, and enables automation
arXiv:2605.03310v1 Announce Type: cross Abstract: Multi-agent LLM systems fail in production at rates between 41% and 87%, mostly due to coordination defects rather than base-model capability. Existin
Corgi Insurance Inc., an artificial intelligence-native insurance carrier built for startups, revealed today that it has raised 160 million in new funding at a 1.3 billion valuation to expand its star
Richard Nieva / Forbes: Corgi, which provides insurance for startups and uses AI to generate quotes, manage claims, and more, raised a 160M Series B led by TCV at a 1.3B valuation — Named after the co
arXiv:2605.03862v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards has become a common way to improve explicit reasoning in large language models, but final-answer correc
Gary Marcus clarifies that in the legal proceeding he's discussing, the jury serves an advisory role while the judge retains decision-making authority on the case outcome. Marcus expresses confidence
Corruption, part N Palm Beach International Airport is now officially renamed to Donald J. Trump International Airport. The airport will be required to purchase official Trump merchandise, directly vi
Corruption, part N+1 Someone quietly placed a massive $920 million crude oil short at 3:40 a.m. ET this morning. Just 70 minutes later, Axios reported the U.S. and Iran were close to a 14 point deal t
Tomofun, the Taiwan-headquartered pet-tech startup behind the Furbo Pet Camera, is redefining how pet owners interact with their pets remotely. To reduce costs and maintain accuracy, Tomofun turned to
arXiv:2605.02603v1 Announce Type: new Abstract: Automated planning traditionally assumes that all aspects of a planning task (initial state, goals, and available actions) are fully specified in advanc
On May 6, 2026, the U.S. Court of Appeals for the Eighth Circuit vacated the FCC's rules prohibiting digital discrimination in broadband access . The court held that the FCC erred by adopting a dispar
arXiv:2605.02218v1 Announce Type: new Abstract: Vision-language models (VLMs) have demonstrated strong capabilities in multimodal perception and reasoning. However, deploying large VLMs on mobile devi
Create the viral Cinemagraph Effect with one click. Upload your image, describe the motion, generate. Seedance 2.0 does the rest. Still photo. Subtle loop. Seamless motion. No restrictions. Try the wo
arXiv:2605.02910v1 Announce Type: cross Abstract: Recent advances in large language models have led to strong performance on reasoning and environment-interaction tasks, yet their ability for creative
arXiv:2605.02080v1 Announce Type: cross Abstract: Drawing on crip theory, this paper proposes cripping AI as a guiding framework to center lived disability experiences in AI research and development.
arXiv:2605.03259v1 Announce Type: new Abstract: High-throughput plant phenotyping, the quantitative measurement of observable plant traits, is critical for modern breeding but remains constrained by a
arXiv:2605.03476v1 Announce Type: new Abstract: Discharge summaries require extracting critical information from lengthy electronic health records (EHRs), a process that is labor-intensive when perfor
arXiv:2605.01892v1 Announce Type: new Abstract: European financial institutions face mounting regulatory pressure while their security operations centres remain constrained not by data or staffing but
arXiv:2605.03544v1 Announce Type: new Abstract: Foundation models with visual question answering capabilities for digital pathology are emerging. Such unprecedented technology requires independent ben
arXiv:2602.16075v2 Announce Type: replace-cross Abstract: Analog processing-using-memory (PUM; a.k.a. in-memory computing) makes use of electrical interactions inside memory arrays to perform bulk mat
arXiv:2605.01777v1 Announce Type: cross Abstract: An evolution of Wireless Communications towards 5G and beyond provides improved user experience in terms of quality of services. Understanding and est
arXiv:2605.02503v1 Announce Type: new Abstract: Evaluating autonomous data analysis agents requires testing their ability to perform exploratory analysis in underexplored data environments. However, m
arXiv:2605.01789v1 Announce Type: new Abstract: Constructing controllable visual data is a major bottleneck for image editing and multimodal understanding. Useful supervision is rarely produced by a s
arXiv:2605.02658v2 Announce Type: new Abstract: Shortcut learning causes deep learning models to rely on non-essential features within the data. However, its formation in deep neural network training
arXiv:2605.02909v1 Announce Type: new Abstract: Reinforcement Learning with Verifiable Rewards (RLVR) has become a powerful approach for improving the reasoning capabilities of large language models (
The general-purpose data center computing environment is taking on a new role as the AI factory, transforming data into intelligence at industrial scale. The rise of the AI factory has captured the at
Boris Cherny acknowledges that recent demand for his product or service has exceeded available capacity, resulting in user frustration. He expresses appreciation for customer feedback and loyalty duri
arXiv:2605.02935v1 Announce Type: new Abstract: In the era of big data, large-scale machine learning models have revolutionized various fields, driving significant advancements. However, large-scale m
arXiv:2602.20078v3 Announce Type: replace-cross Abstract: Scaling cooperative multi-agent reinforcement learning (MARL) is fundamentally limited by cross-agent noise. When agents share a common reward
arXiv:2605.03610v1 Announce Type: new Abstract: Shadows cast by terrain and tall structures remain a major obstacle for high-resolution satellite image analysis, degrading classification, detection, a
arXiv:2603.20151v2 Announce Type: replace-cross Abstract: Engineering system design -- whether mechatronic, control, or embedded -- often proceeds in an ad hoc manner, with requirements left implicit
arXiv:2605.03472v1 Announce Type: new Abstract: As conversational AI therapists are increasingly used in psychological support settings, reliable offline evaluation of therapeutic response quality rem
Devin Review is now live in Windsurf, alongside Quick Review: a fast local bug detector powered by SWE-check. Fast and comprehensive code review and fixes are now available right in your IDE. Devin Re
Devin Review runs hundreds of thousands of times per day. Starting today, run it directly from Windsurf: a smart reviewer in your editor, with bugs and context in one place. Also launching Quick Revie
The rise of AI coding agents has commoditized code generation, exposing a deeper challenge for software teams: the non-coding friction that consumes the vast majority of a developer’s day. Fixing that
arXiv:2605.03327v1 Announce Type: new Abstract: Reinforcement learning is crucial for aligning large language models to perform complex reasoning tasks. However, current algorithms such as Group Relat
arXiv:2605.01338v1 Announce Type: new Abstract: System-level diagrams encode the architectural blueprint of chip design, specifying module functions, dataflows, and interface protocols. However, non-s
arXiv:2605.03639v1 Announce Type: new Abstract: Dynamic point cloud pretraining is still dominated by masked reconstruction objectives. However, these objectives inherit two key limitations. Existing
arXiv:2605.03175v1 Announce Type: new Abstract: The remote sensing (RS) domain suffers from a lack of densely labeled datasets, which are costly to obtain. Thus, models that can segment RS imagery wel
arXiv:2509.15692v2 Announce Type: replace-cross Abstract: Simultaneous speech-to-text translation (Simul-S2TT) aims to translate speech into target text in real time, outputting translations while rec
arXiv:2605.01794v1 Announce Type: cross Abstract: Efficient radar resource allocation is a fundamental yet computationally challenging problem, as optimal solutions typically require iterative optimiz
arXiv:2605.03408v1 Announce Type: new Abstract: Reinforcement learning systems rely on environment interfaces that specify observations and reward functions, yet constructing these interfaces for new
arXiv:2605.02949v1 Announce Type: new Abstract: We propose a novel method of understanding disease transformation from a healthy baseline with biomarker-level explainability. By modeling the biomarker
arXiv:2605.01899v1 Announce Type: new Abstract: The growing capabilities of large language models (LLMs) have driven their widespread deployment across diverse domains, even in potentially high-risk s
arXiv:2605.03570v1 Announce Type: new Abstract: Real-world clinical data is inherently multimodal, providing complementary evidence that mirrors the practical necessity of jointly assessing multiple r
arXiv:2605.02290v1 Announce Type: new Abstract: Distilling large reasoning models is essential for making Long-CoT reasoning practical, as full-scale inference remains computationally prohibitive. Exi
arXiv:2605.03069v1 Announce Type: cross Abstract: Federated learning (FL) lets distributed nodes train a shared model without exchanging their raw data, but in privacy-sensitive deployments medical se
arXiv:2605.03313v1 Announce Type: new Abstract: Privacy concerns in distributed learning often lead clients to return intentionally altered gradient information. We consider the problem of learning co
arXiv:2605.03722v1 Announce Type: new Abstract: We propose Evolutionary Dynamic Loss (EDL), a framework that learns a transferable classification loss in the probability space using unlimited syntheti
arXiv:2605.03877v1 Announce Type: new Abstract: Dataset distillation enables efficient training by distilling the information of large-scale datasets into significantly smaller synthetic datasets. Dif
arXiv:2605.03255v1 Announce Type: new Abstract: The rise of Large Language Models (LLMs) has sparked debate about whether these systems exhibit human-level cognition. In this debate, little attention
arXiv:2601.21684v2 Announce Type: replace Abstract: Test-Time Scaling enhances the reasoning capabilities of Large Language Models by allocating additional inference compute to broaden the exploration
arXiv:2605.02163v1 Announce Type: cross Abstract: Software documentation frequently drifts from executable logic as codebases evolve, creating technical debt that degrades maintainability and causes d
arXiv:2605.03281v1 Announce Type: cross Abstract: Donor-level disease classification from single-cell RNA sequencing (scRNA-seq) requires strict donor-aware cross-validation: naive pipelines that spli