AI news archive.
10,661 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchDesigning a Boundary Negotiating Artifact for Collaborative Socio-Technical Sense-Making in AI Regulatory Sandboxes
arXiv:2609.37109v1 Announce Type: cross Abstract: The rapid, unpredictable advancements in AI system capabilities has seen regulators take adaptive and experimental approaches to policymaking. Established in other domain…
- arXiv cs.AIresearchMultichannel Audio Quality Assessment: Extending Pretrained Perceptual Models to Spatial Audio
arXiv:2609.37116v1 Announce Type: cross Abstract: Accurate perceptual quality assessment is essential for evaluating and optimizing spatial audio, where perceived quality depends on both signal fidelity and inter-channel…
- arXiv cs.AIresearchUnlocking the Critic: Reward-Free Policy Optimization for LLM Post-Training
arXiv:2609.37119v1 Announce Type: cross Abstract: Recent approaches to reinforcement learning (RL) post-training for large language models increasingly remove the critic to reduce training instability and memory overhead…
- arXiv cs.AIresearchSQUARE: Structured Quantum Representation Adapters as Compact Quadratic Feature Maps for Frozen Language Models
arXiv:2609.37134v1 Announce Type: cross Abstract: Frozen language models (LMs) are increasingly used as fixed feature extractors for downstream reranking, scoring, and preference modeling, raising a practical question: h…
- arXiv cs.AIresearchTrajectory Soup: Pushing the Compute-Scaling Frontier of LLM Mid-training via Diverse Trajectories
arXiv:2609.37169v1 Announce Type: cross Abstract: Mid-training equips pretrained large language models with specialized and reasoning capabilities, but the returns of this stage are bounded since additional serial comput…
- arXiv cs.AIresearchInterpolated Policy Distillation: A Controllable Continuum Between Off-Policy and On-Policy Distillation
arXiv:2609.37170v1 Announce Type: cross Abstract: Off-policy and on-policy distillation have traditionally been formulated as separate paradigms, each favoring a different property of distillation trajectories. Teacher-g…
- arXiv cs.AIresearchEgoHumanoid-V2: Human-to-Humanoid Transfer of Coordinated Whole-Body Skills for Loco-Manipulation
arXiv:2609.37181v1 Announce Type: cross Abstract: Human demonstrations capture diverse scenes and rich whole-body skills without requiring robot teleoperation. Prior work on egocentric transfer has emphasized scene gener…
- arXiv cs.AIresearchCRJudgeBench: Can AI Detect Plausible but Invalid Code Reviews?
arXiv:2609.37216v1 Announce Type: cross Abstract: Large language models can generate plausible code-review comments, but such comments may contain technically incorrect claims that mislead developers. We study technical…
- arXiv cs.AIresearchBeyond Semantic Narrowing: Robust and Efficient LLM Watermarking with Hamming Neighborhoods
arXiv:2609.37218v1 Announce Type: cross Abstract: Semantic watermarking improves robustness against watermark removal attacks by embedding detectable signals into sentence-level representations. However, existing waterma…
- arXiv cs.AIresearchResComEmb: Effective and Efficient Multimodal Embedding via Residual Homogeneity Compression
arXiv:2609.37225v1 Announce Type: cross Abstract: Multimodal large language models (MLLMs) have shown strong potential for universal multimodal representation learning. However, existing methods either compress each inpu…
- arXiv cs.AIresearchDatalogBench: Evaluating Large Language Models on Text-to-Datalog Synthesis
arXiv:2609.37233v1 Announce Type: cross Abstract: Datalog underpins reasoning tasks such as program analysis, but its programs are hard to write. Existing synthesizers automate this task but require users to state their…
- arXiv cs.AIresearchCodebook-Guided Cross-Modal Knowledge Distillation for Structurally Heterogeneous Features
arXiv:2609.37243v2 Announce Type: replace-cross Abstract: Cross-modal knowledge distillation transfers knowledge from a teacher modality to a student modality. Existing feature-level alignment methods typically assume th…
- arXiv cs.AIresearchV-JEPA Policy: Building Effective World-Action Models on Predictive Visual Latents
arXiv:2609.37250v2 Announce Type: replace-cross Abstract: World-action models (WAMs) couple future visual-state prediction with action generation. By adapting video generators or image-editing models pretrained at scale,…
- arXiv cs.AIresearchLoss-Guided Pretraining Data Selection for Time-Series Foundation Models
arXiv:2609.37255v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) are pretrained on heterogeneous collections containing billions of observations, yet their training windows are typically sampled wi…
- arXiv cs.AIresearchUniAfford: Token-Routed Multitask Learning for Generalizable 2D-3D Affordance Perception
arXiv:2609.37264v1 Announce Type: cross Abstract: Affordance perception aims to localize actionable regions supporting embodied interaction, yet 2D and 3D affordance grounding have evolved as separate problems, with diff…
- arXiv cs.AIresearchVISTA-Bench: Benchmarking Multilingual Image Translation with Image-Specific Rubrics
arXiv:2609.37287v1 Announce Type: cross Abstract: Image translation is a fundamental capability of multimodal models for multilingual applications, requiring visual understanding and meaning preservation across languages…
- arXiv cs.AIresearchHidden Reasoning Must Leak, but Need Not Be Readable: Fundamental Opportunities and Limits for Chain-of-Thought Monitoring
arXiv:2609.37312v1 Announce Type: cross Abstract: Can reasoning models trick chain of thought (CoT) monitors and perform hidden computation without revealing it in their thinking traces? We show that the answer depends o…
- arXiv cs.AIresearchA Sharp Transition in Data Reconstruction under Differential Privacy
arXiv:2609.37344v1 Announce Type: cross Abstract: Data reconstruction attacks have empirically been successful in recovering training samples from learned models, raising privacy concerns and motivating defenses with gua…
- arXiv cs.AIresearchTAEC: Trajectory-Aware Evidence Coordination for Multi-Step Visual RAG
arXiv:2609.37349v1 Announce Type: cross Abstract: Multi-step visual retrieval-augmented generation (RAG) answers complex questions by repeatedly retrieving visual evidence, updating an intermediate state, and deciding wh…
- arXiv cs.AIresearchPort-Hamiltonian Latent Deliberation: Mitigating the Deliberation Drift Cliff in Test-Time Compute Scaling
arXiv:2609.37351v1 Announce Type: cross Abstract: Test-time compute scaling has emerged as a cornerstone of advanced machine reasoning, yet performing iterative deliberation directly within continuous latent representati…
- arXiv cs.AIresearchCompiling Learning Problems into Adaptation Programs for Language Models
arXiv:2609.37371v1 Announce Type: cross Abstract: Model adaptation is typically governed by a fixed recipe, even though different update programs can produce substantially different behavioral outcomes. We introduce adap…
- arXiv cs.AIresearchDo-JEPA: From Masking to Intervention in Latent World Models
arXiv:2609.37378v1 Announce Type: cross Abstract: Latent world models are trained to predict what happens next, so nothing in their objective separates what an action caused from what merely co-occurred with it. Object-m…
- arXiv cs.AIresearchComplexity-Aware Evaluation of LLM Comprehension
arXiv:2609.37405v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for software engineering tasks that require understanding existing source code, including behavior prediction, function…
- arXiv cs.AIresearchSimultaneous Neural Optimal Transport
arXiv:2609.37424v1 Announce Type: cross Abstract: Optimal Transport (OT) provides a principled framework for learning transformations between probability distributions from unpaired samples. In many applications, however…
- arXiv cs.AIresearchLazySloth: Bounded LLM-based Lazy Tree Search for Fast Long Video Comprehension
arXiv:2609.37426v1 Announce Type: cross Abstract: Modern vision-language models (VLMs) have shown promising results in long-video understanding due to the rich semantic information they can capture. However, most methods…
- arXiv cs.AIresearchLearning to Retrieve Missing Evidence for Long-Term Memory QA
arXiv:2609.37443v1 Announce Type: cross Abstract: Long-term memory enables language models to use past interactions in future conversations. However, evidence needed to answer a question may be scattered across distant t…
- arXiv cs.AIresearchEngineering Efficient Self-Play Chess: Search, Replay, and Throughput Under Limited Compute
arXiv:2609.37447v1 Announce Type: cross Abstract: How strong can an AlphaZero-style chess system become under limited training compute when its entire learning loop is engineered for efficiency? We train from random init…
- arXiv cs.AIresearchRegime Boundary Alignment for Evidence-Gated Question Answering
arXiv:2609.37491v1 Announce Type: cross Abstract: Retrieval-augmented language models are expected to answer from the retrieved evidence, but in practice they often keep answering when that evidence is missing. We trace…
- arXiv cs.AIresearchRisk-Controlled Selective LLM Answering by Pricing Label-Free Checks
arXiv:2609.37493v1 Announce Type: cross Abstract: Serving an answer from a large language model requires deciding when to abstain, yet a verifier's ranking accuracy alone does not determine the error rate among served an…
- arXiv cs.AIresearchHierarchical Compression of Vision-Language Model Benchmarks
arXiv:2609.37515v1 Announce Type: cross Abstract: Thorough evaluation of vision-language models (VLMs) has become prohibitively expensive, as benchmarks span an ever-broader spectrum of capabilities and new models arrive…
- arXiv cs.AIresearchVideo2STL: Grounding VLM-Generated Temporal Specifications for Robot Learning
arXiv:2609.37519v1 Announce Type: cross Abstract: Video-based policy learning is particularly promising, as it illustrates target behaviors without requiring action annotations or embodiment-matched demonstrations. A cen…
- arXiv cs.AIresearchDScale: Scaling Block-Diffusion Speculative Decoding with Adaptive Verification
arXiv:2609.37532v1 Announce Type: cross Abstract: Growing large language model applications demand efficient inference. At high concurrency, block-diffusion speculative decoding suffers from verification padding, rejecte…
- arXiv cs.AIresearchRisk-Aware Semantic Grounding for Trustworthy LLM-Based Robot Planning
arXiv:2609.37554v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used as high-level planners in robot navigation, but their outputs may become unreliable when instructions are ambiguous, un…
- arXiv cs.AIresearchTReVS: Integrating Textual Relevance and Visual Saliency for Efficient Vision-Language Model Token Pruning
arXiv:2609.37581v1 Announce Type: cross Abstract: Vision-Language Models (VLMs) excel at visual understanding and reasoning but often incur substantial inference costs due to the large number of visual tokens. Recent vis…
- arXiv cs.AIresearchFedSocket: Recipient-Executable Knowledge Exchange for Heterogeneous Multimodal Federated Learning
arXiv:2609.37582v2 Announce Type: replace-cross Abstract: Federated knowledge must remain usable by recipients with different modalities, private architectures, and tasks. We present FedSocket, which makes recipient exec…
- arXiv cs.AIresearchLearning as Deepfakes Evolve: RF-Prompt for Continual Audio Deepfake Detection
arXiv:2609.37586v1 Announce Type: cross Abstract: Continual audio deepfake detection requires learning newly emerging deepfake methods while retaining discrimination of previously encountered speech. Existing dataset-inc…
- arXiv cs.AIresearchReLMem: Learning Recurrent Memory for Longitudinal EHR Modeling
arXiv:2609.37587v1 Announce Type: cross Abstract: Longitudinal electronic health record (EHR) modeling requires integrating new visits with an expanding patient history. Yet the continual accumulation of clinical informa…
- arXiv cs.AIresearchCredit-Guided Policy Improvement for Test-time Adaptive Vision-Language Navigation
arXiv:2609.37591v1 Announce Type: cross Abstract: Test-time adaptation for vision-language navigation (TTA-VLN) enables pretrained policies to adapt online to unseen environments using only test-time observations and int…
- arXiv cs.AIresearchIndependent Verification Paths Are Not Independent: A Case Study of Common-Mode Failure in a Satellite Catalogue Pipeline
arXiv:2609.37603v1 Announce Type: cross Abstract: A common safeguard for a data pipeline is redundant computation: derive each published number by two routes built on different technology and refuse to exit when they dis…
- arXiv cs.AIresearchAS$^2$D: Accelerating On-Demand Audio Understanding on Mobile Devices
arXiv:2609.37617v1 Announce Type: cross Abstract: Speculative decoding accelerates autoregressive generation by using a smaller drafter to propose tokens for batched verification by a larger target. However, conventional…
- arXiv cs.AIresearchCorrect, Don't Delete: Mitigating Emergent Misalignment with Corrective Supervision
arXiv:2609.37624v1 Announce Type: cross Abstract: Fine-tuning a language model on a narrow set of harmful demonstrations, such as bad medical advice, can make it broadly misaligned on unrelated questions, a phenomenon kn…
- arXiv cs.AIresearchSPLASH: Switching Parallel Layouts of Attention with Seamless Handoff for LLM Serving
arXiv:2609.37626v1 Announce Type: cross Abstract: No single way of parallelizing attention serves large language models well under all loads. Low concurrency favors tensor parallelism, many independent requests favor dat…
- arXiv cs.AIresearchProCTI: Prototype-Refined Global Conditioning for Diffusion-Based Time Series Imputation
arXiv:2609.37632v1 Announce Type: cross Abstract: Time series imputation has progressed from statistical and deep learning approaches to diffusion-based models, which have shown strong recent performance. Existing diffus…
- arXiv cs.AIresearchEvaluating and Benchmarking the System One Model Jev
arXiv:2609.37647v2 Announce Type: replace-cross Abstract: Jev is a commercial "System One" model from TypeSafe AI that does not generate text: given a state and typed questions, it returns a choice from fixed options, a…
- arXiv cs.AIresearchSemantic Map Sharing and Capability-Aware Coverage Planning for AI-Native 6G Robotic Coordination
arXiv:2609.37666v1 Announce Type: cross Abstract: Search and Rescue (SAR) operations increasingly deploy heterogeneous teams of aerial and ground robots. However, conventional coverage methods typically do not translate…
- arXiv cs.AIresearchRetrieve, Reproduce, Reveal: Dissecting Retrieval-Augmented Software Vulnerability Detection
arXiv:2609.37669v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) is increasingly used to enhance Large Language Model (LLM)-based software vulnerability detection by grounding predictions in retriev…
- arXiv cs.AIresearchWhen Models Don't Manipulate Manifolds: The Geometry of a Comparison Task
arXiv:2609.37680v1 Announce Type: cross Abstract: One of the current premises of mechanistic interpretability research is that detailed accounts of the geometry of neural network representations can tell us how models pe…
- arXiv cs.AIresearchGARDiff: Graph-Aligned Residual Diffusion for Probabilistic Multivariate Time-Series Forecasting
arXiv:2609.37694v1 Announce Type: cross Abstract: Diffusion models have recently shown strong potential for probabilistic multivariate time-series forecasting by modeling complex conditional distributions. Recent decoupl…
- arXiv cs.AIresearchWidth Expansion as a Method for Class Incremental Learning
arXiv:2609.37702v1 Announce Type: cross Abstract: Class Incremental Learning (Class-IL) requires models to learn new classes over time while preserving previously acquired knowledge without access to past data or task id…
- arXiv cs.AIresearchVIF-Bench: Evaluating Visual Instruction Following in Multi-Reference Image Generation
arXiv:2609.37709v1 Announce Type: cross Abstract: Recent multimodal image generation models can take multiple images and textual instructions as input, enabling reference-based generation guided not only by text but also…