AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchSpeedbumps: Rejection Attacks on Speculative Decoding
arXiv:2610.10929v1 Announce Type: cross Abstract: Speculative decoding is a popular technique for increasing the speed and reducing the costs of large language model (LLM) inference by verifying multiple draft tokens in…
- arXiv cs.AIresearchRethinking the Tradeoff Between Temporal Encoding and Nonlinear Computation in Spiking Language Models
arXiv:2610.10933v1 Announce Type: cross Abstract: Spiking language models face a tradeoff between representing continuous semantic features over short temporal windows and retaining costly nonlinear attention operations.…
- arXiv cs.AIresearchTRACE: A Governance Framework for Measuring Explainability Debt in Production AI Systems
arXiv:2610.10957v1 Announce Type: cross Abstract: Production AI systems deployed in high-stakes domains accumulate a governance liability that existing monitoring frameworks fail to detect: the progressive inability to e…
- arXiv cs.AIresearchWhen Citations Mislead? A Claim-Level Benchmark for Legal Hallucination Detection
arXiv:2610.10971v1 Announce Type: cross Abstract: Large language models are increasingly used in legal research and drafting, but they can still produce claims that sound convincing without being supported by the cited s…
- arXiv cs.AIresearchBudgeted Multi-Source Counterfactual Annotation for Off-Policy Evaluation
arXiv:2610.10974v1 Announce Type: cross Abstract: Off-policy evaluation (OPE) estimates the value of a target policy from logged data, but limited behavior-policy coverage can force high-variance reweighting or reward-mo…
- arXiv cs.AIresearchOptimizing Large Language Models with Chained LMOs
arXiv:2610.10975v1 Announce Type: cross Abstract: Muon has motivated a growing family of optimizers that compose multiple matrix normalizations, but these methods remain fragmented and lack a unified perspective. We intr…
- arXiv cs.AIresearchProbabilistic Sensing, Deterministic Authority: Admitting Model-Produced Observations into Sufficiency-Checked Governance Contracts
arXiv:2610.10978v1 Announce Type: cross Abstract: When a field that an authority contract needs exists only in unstructured evidence, a model can sense it. We admit the model's output only as an observation record with a…
- arXiv cs.AIresearchMid-Training Language Models on Raw Video
arXiv:2610.11019v1 Announce Type: cross Abstract: Multimodal large language models learn mostly from paired image-text data or annotated video, and raw web video is rarely used to further train an existing language model…
- arXiv cs.AIresearchIntent Graph: Navigating the Analytical Reasoning Space for Exploratory Data Analysis
arXiv:2610.11025v1 Announce Type: cross Abstract: Exploratory data analysis (EDA) is rarely open-ended in practice: analysts work from high-level domain questions toward the concrete analyses that can answer them, priori…
- arXiv cs.AIresearchLanguage Modeling is Monotone Compression
arXiv:2610.11031v1 Announce Type: cross Abstract: A long-standing hypothesis in artificial intelligence and neuroscience posits that intelligence is closely related to compression: the ability to compress information eff…
- arXiv cs.AIresearchEmergent Inverse-Depth Scaling From Nonlinearity In Attention
arXiv:2610.11063v1 Announce Type: cross Abstract: Scaling laws describe power-law improvements in model performance with dataset size and parameter count, yet their underlying mechanisms are not fully understood. To expl…
- arXiv cs.AIresearchStability-Plasticity Balance via Singular-Vector Selection in LLM Continual Learning
arXiv:2610.11076v1 Announce Type: cross Abstract: Domain-specific continual adaptation of LLMs risks catastrophic forgetting, creating a fundamental tension between acquiring new capabilities and preserving those learned…
- arXiv cs.AIresearchContinuous Ground-Truth Construction and a Recovery Policy for Air--Water Robotic Tracking
arXiv:2610.11096v2 Announce Type: replace-cross Abstract: Visual tracking across the air-water interface is challenged by splashes, bubbles, refraction, reflections, and abrupt appearance changes that can temporarily inv…
- arXiv cs.AIresearchSFT-as-Context Mitigates Forgetting in Supervised Fine-Tuning
arXiv:2610.11132v1 Announce Type: cross Abstract: Supervised fine-tuning (SFT) equips large language models (LLMs) with specialized capabilities, but often comes at the cost of forgetting the general capabilities of thei…
- arXiv cs.AIresearchImproving Image-Based Nutrition Estimation Through Multimodal Food-Item Verification and Recovery
arXiv:2610.11144v1 Announce Type: cross Abstract: Single-image nutrition estimation can fail silently when visible foods are missed. Even when a food is correctly identified, its proposed region may not support portion e…
- arXiv cs.AIresearchSP-DocReader: Difference-Aware Self-Play for Precise Document OCR
arXiv:2610.11148v1 Announce Type: cross Abstract: Accurate page transcription remains difficult for vision language models under limited input and training budgets. We present SP-DocReader, a self-play framework for opti…
- arXiv cs.AIresearchCARE: Constrained Attention Refinement for Fine-Grained Visual Classification via Teacher-Student Distillation
arXiv:2610.11153v1 Announce Type: cross Abstract: Fine-grained visual classification requires models to recognize subtle local traits while exposing the visual evidence behind their predictions. Class-specific attention…
- arXiv cs.AIresearchCharacterizing Statistical Separability in TP-CRIV for Probabilistic AI Models
arXiv:2610.11163v2 Announce Type: replace-cross Abstract: Third-party challenge-response identity verification (TP-CRIV) enables an independent verifier to assess whether a claimant possesses a model identical to a remot…
- arXiv cs.AIresearchPIVOT: Perplexity-Informed KD-to-RL Transition Scheduling for Vertical-Domain Few-Shot Distillation
arXiv:2610.11167v1 Announce Type: cross Abstract: Vertical-domain few-shot classification remains challenging for small language models, as limited supervision makes it difficult to acquire domain-specific decision knowl…
- arXiv cs.AIresearchPMTRM: Pseudo-Memory Temporal Re-encoding Module for Embodied Policy Learning
arXiv:2610.11168v1 Announce Type: cross Abstract: Robotic manipulation often contains repeated motions whose local observations look similar at different phases. When these phases require different actions, a policy that…
- arXiv cs.AIresearchHigher-Order Action Supervision Makes A Strong Policy Class
arXiv:2610.11175v2 Announce Type: replace-cross Abstract: Modern data-driven decision-making methods, such as imitation learning (IL) and reinforcement learning (RL), have achieved great success in solving many complex t…
- arXiv cs.AIresearchRAG-Stress: Probing the Limits of Evidence Reliance in Retrieval-Augmented Generation
arXiv:2610.11183v1 Announce Type: cross Abstract: Following retrieved evidence does not guarantee factual correctness: misleading evidence can induce a model to replace an answer it previously gave correctly. Standard ac…
- arXiv cs.AIresearchSafeInferCom: Safe Inference-Time Compute via Verifier-Guided Mid-Generation Intervention for Robotic Task Planning
arXiv:2610.11223v1 Announce Type: cross Abstract: Large Reasoning Language Models (LRLMs) enable multi-step reasoning for robotic task planning, but continued reasoning can overwrite valid intermediate plans or leave con…
- arXiv cs.AIresearchNeuro-Memory Fuzzy Inference System for Mimicking Human-like Car Following Behavior
arXiv:2610.11252v1 Announce Type: cross Abstract: This study presents the Neuro-Memory Fuzzy Inference System (NeMeFIS), a hierarchical machine learning architecture that asymmetrically models acceleration and decelerati…
- arXiv cs.AIresearchGated Memory: Admission-Controlled Memory Formation for Conversational AI
arXiv:2610.11270v1 Announce Type: cross Abstract: Personalized conversational AI relies on long-term memory systems that extract facts from user utterances and store them in persistent vector stores. Despite progress in…
- arXiv cs.AIresearchHow to post-train on a surrogate: Envelope sampling mitigates reward hacking
arXiv:2610.11281v1 Announce Type: cross Abstract: Large language models (LLMs) are commonly post-trained against LLM judges and other cheap surrogates because the true reward, such as human preference, is too expensive t…
- arXiv cs.AIresearchDynaTE: Accelerating Diffusion LLMs via Dynamic Token Execution
arXiv:2610.11284v1 Announce Type: cross Abstract: Diffusion-based LLMs (dLLMs) have recently emerged as a promising alternative to autoregressive (AR) LLMs by enabling bidirectional parallel refinement, alleviating the s…
- arXiv cs.AIresearchCharacterizing Overconfident Failure in LLM-Based Code Generation
arXiv:2610.11300v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for automated code generation, but generated programs can appear syntactically plausible while still failing execution-…
- arXiv cs.AIresearchFrom Geometry to Generalization: Why Row Normalization Can Beat Adam and Muon
arXiv:2610.11309v1 Announce Type: cross Abstract: Different optimizers can fit the same training data while selecting classifiers with substantially different geometries, but whether this difference provably affects popu…
- arXiv cs.AIresearchMetaEncoder: Exploring the Limit of Bi-Encoders for Multimodal System One Decision Making with Natural Language Interface
arXiv:2610.11316v1 Announce Type: cross Abstract: System One models output constrained decisions and probability distributions rather than free-form text generation. While prevailing paradigms rely on structured schema o…
- arXiv cs.AIresearchRethinking Contrastive Loss in CLIP Post-training: A Complementary Framework with Frozen Text Encoder
arXiv:2610.11374v2 Announce Type: replace-cross Abstract: CLIP serves as a foundational vision-language model and the de facto vision encoder for downstream VLMs such as LLaVA. Post-training offers a lightweight route to…
- arXiv cs.AIresearchCRISP: Fixing Flying Pixels in Latent LiDAR Generation via Diffusion Decoding
arXiv:2610.11376v2 Announce Type: replace-cross Abstract: Latent LiDAR pipelines suffer from flying pixels: convolutional VAEs blur sharp radial depth discontinuities, yielding edge depths that back-project to points flo…
- arXiv cs.AIresearchEvoKnow: Continual Knowledge Evolution for AI-Generated Image Detection
arXiv:2610.11381v1 Announce Type: cross Abstract: AI-generated image detectors are commonly trained on fixed generator domains and become difficult to maintain as new generative models emerge. Continual adaptation is cha…
- arXiv cs.AIresearchRISR: Residual-Informed Scientific Equation Discovery with Large Language Models
arXiv:2610.11387v1 Announce Type: cross Abstract: Symbolic regression combines structural search with numerical fitting, but aggregate fit scores do not describe how the remaining error varies across inputs. We introduce…
- arXiv cs.AIresearchRewiring Semantics, Dynamics, and Control: A Simple yet Effective Action-Centric Tri-Stream Transformer
arXiv:2610.11416v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have emerged as a prominent framework for complex robotic manipulation, building on the strong semantic understanding of pretrained Vi…
- arXiv cs.AIresearchMissing Modality-Aware Calibration for Trustworthy Brain Tumor Segmentation
arXiv:2610.11419v1 Announce Type: cross Abstract: Multimodal brain tumor segmentation typically leverages multiple MRI modalities, yet incomplete modality acquisition is common in clinical practice due to protocol hetero…
- arXiv cs.AIresearchZatom-2: Multitask Pretraining on Atomistic Data for Generative Modeling across Domains
arXiv:2610.11454v2 Announce Type: replace-cross Abstract: Unified atomistic modeling has the potential to accelerate discovery in chemistry, materials science, and biology by bridging data-rich chemical domains and data-…
- arXiv cs.AIresearchGenerative Adversarial Loops
arXiv:2610.11458v1 Announce Type: cross Abstract: AI research progress can be viewed as the interaction between two processes: benchmark creation and method discovery. Historically, both were driven by human intelligence…
- arXiv cs.AIresearchProtoSemImage: Image-Valued Prototypes with Deformable Row Alignment for Interpretable Document Classification
arXiv:2610.11460v1 Announce Type: cross Abstract: Prototypes in classification models are almost always vectors, and a vector has no readable form. This paper asks what happens when a prototype is an image. Documents giv…
- arXiv cs.AIresearchConditional Residual Prediction: Improving Autoregressive Video Diffusion without a Bidirectional Teacher
arXiv:2610.11479v1 Announce Type: cross Abstract: Causal video diffusion models generate video autoregressively, which suits streaming, interactive, and long-video generation. Under standard training, however, they often…
- arXiv cs.AIresearchCompactness and Consistency: A Conjoint Framework for Deep Graph Clustering
arXiv:2610.11506v1 Announce Type: cross Abstract: Graph clustering is a fundamental task in data analysis, aiming at grouping nodes with similar characteristics in the graph into clusters. This problem has been widely ex…
- arXiv cs.AIresearchMSGAT: Multi-Head Spiking Graph Attention with Similarity-Space Fusion for Image-Text Retrieval
arXiv:2610.11526v1 Announce Type: cross Abstract: Spiking neural networks (SNNs) offer an energy-efficient computing paradigm through sparse event-driven computation, showing great potential for efficient multimodal lear…
- arXiv cs.AIresearchDesign Creativity Bench: Measuring creativity in LLM-Generated UI
arXiv:2610.11539v2 Announce Type: replace-cross Abstract: As leading LLMs improve on capability evaluations, their limitations in producing creative outputs on design tasks remain insufficiently characterised. Our work i…
- arXiv cs.AIresearchLearning to Orchestrate Evolutionary Search: Progression-Aware Deep Reinforcement Learning for Dynamic DE-CMA-ES Coordination in Optimization and Structural Model Updating
arXiv:2610.11546v2 Announce Type: replace-cross Abstract: Solving high-dimensional structural model updating problems requires an algorithm capable of navigating complex, non-convex landscapes with correlated parameters.…
- arXiv cs.AIresearchSera: Semantic Representation Aggregation with Knowledge and LLM for Reliable and Interpretable Battery Health Forecasting
arXiv:2610.11567v3 Announce Type: replace-cross Abstract: Battery state of health (SoH) forecasting is important for battery management, but remains challenging due to nonlinear degradation and heterogeneity across batte…
- arXiv cs.AIresearchAdapting English Quality Classifiers for Multilingual LLM Pretraining Data Selection
arXiv:2610.11585v1 Announce Type: cross Abstract: Recent advances in large language model (LLM) pretraining highlight the role of high-quality training data in improving performance. While model-based filtering has prove…
- arXiv cs.AIresearchLarge Language Model Turnover Undermines Screening for Artificial Intelligence-Assisted Scientific Writing
arXiv:2610.11599v1 Announce Type: cross Abstract: Journals and conferences have begun to screen submitted manuscripts for text written using large language models (LLMs). The reliability of this screening rests on benchm…
- arXiv cs.AIresearchNanoProof: Open and Efficient Automated Theorem Proving in Lean 4
arXiv:2610.11605v1 Announce Type: cross Abstract: We introduce NanoProof, to our knowledge the first factorized execution-guided theorem prover in Lean 4 whose training data, extraction tooling, training pipeline, and we…
- arXiv cs.AIresearchBeyond Report Imitation: Clinically Aware Multi-Image Ultrasound Report Generation from Visible Evidence
arXiv:2610.11610v1 Announce Type: cross Abstract: Generating ultrasound reports from multiple images requires aggregating clinical evidence across views, yet archived key frames capture only part of the dynamic examinati…
- arXiv cs.AIresearchTAM: Task-Aware Memory Distillation for Efficient Spatiotemporal Prediction
arXiv:2610.11617v1 Announce Type: cross Abstract: Knowledge distillation enables efficient spatiotemporal prediction by transferring knowledge from an accurate teacher to a compact student. However, matching outputs or f…