AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchParallelizable Probabilistic Latent Reasoning for Diverse Reasoning Trajectories
arXiv:2610.29385v2 Announce Type: replace-cross Abstract: Language models relying on verbalized Chain-of-Thought (CoT) are constrained to token-by-token generation in the language space, where many tokens serve textual c…
- arXiv cs.AIresearchLLMSeg: Training-Free Text-Prompted Image Segmentation with B-Splines
arXiv:2610.29409v1 Announce Type: cross Abstract: Promptable segmentation models such as SAM 3 achieve remarkable open-vocabulary performance but require dedicated architectures, large-scale annotation engines, and task-…
- arXiv cs.AIagentsBeyond Small Talk: Modeling Disclosure Trajectories in Human-AI Conversation
arXiv:2610.29413v1 Announce Type: cross Abstract: Recently, we see a rise in conversational agents as a form of social and emotional support, where disclosure will unfold over time. Yet, current evaluations of these agen…
- arXiv cs.AIagentsRegoMender: A Multi-agent Framework for Automated Rego Policy Repair
arXiv:2610.29456v1 Announce Type: cross Abstract: Policy-as-Code (PaC) has emerged as a foundational paradigm in cloud-native systems. However, repairing Rego policies remains challenging due to their strict syntax, decl…
- arXiv cs.AIagentsHarness Scaling for Generalizable Agentic Reinforcement Learning
arXiv:2610.29458v2 Announce Type: replace-cross Abstract: Agent harnesses have become a central component of modern agentic systems, shaping how models use tools, manage context, and coordinate long-horizon interaction.…
- arXiv cs.AIresearchOmniSimulator: Aligning Small Language Models for Authentic Heterogeneous Behavior Modeling
arXiv:2610.29472v1 Announce Type: cross Abstract: Large language models (LLMs) have shown great potential as general-purpose user simulators for interactive systems. Prior studies have demonstrated that training on high-…
- arXiv cs.AIresearchGenerative Modeling via Nonlinear Schr\"odinger Bridges and Branching Diffusions
arXiv:2610.29476v1 Announce Type: cross Abstract: We propose a new generative modeling framework grounded in forward-backward partial differential equations (PDEs). These equations arise naturally in mean-field game (MFG…
- arXiv cs.AIresearchA Strong MoE Is All You Need for Process Supervision
arXiv:2610.29498v1 Announce Type: cross Abstract: Process reward models (PRMs) provide fine-grained supervision for multi-step reasoning, yet obtaining reliable process labels remains a central bottleneck. Existing appro…
- arXiv cs.AIagentsRethinking Agentic Model Orchestration for Time Series Forecasting
arXiv:2610.29504v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) perform unevenly across forecasting tasks. Recent work uses agentic model orchestration (AMO) to select or combine TSFMs, often outp…
- arXiv cs.AIresearchKeeping Time vs. Understanding Time: Neither Alone Explains Temporal Reasoning in LLMs
arXiv:2610.29507v1 Announce Type: cross Abstract: Temporal reasoning is widely assumed to decompose into two modes: temporal arithmetic (date and time calculations), and temporal semantics (understanding temporal and cau…
- arXiv cs.AIresearchMitigating Query Shortcuts in Chain-of-Thought with Context-Aware Decoding
arXiv:2610.29518v1 Announce Type: cross Abstract: While Chain-of-Thought (CoT) prompting improves the reasoning performance of large language models (LLMs), recent studies have shown that final answers do not always depe…
- arXiv cs.AIresearchAre Joint-Embedding Predictive Objectives Effective for Longitudinal EHRs?
arXiv:2610.29528v1 Announce Type: cross Abstract: Masked language modelling (MLM) is the dominant pretraining objective for transformer encoders applied to longitudinal electronic health records (EHRs). However, reconstr…
- arXiv cs.AIresearchBlock Diffusion for Longitudinal EHR: Accuracy, Efficiency, and Representation Trade-offs
arXiv:2610.29533v1 Announce Type: cross Abstract: Autoregressive (AR) models have proved effective for zero-shot prediction from longitudinal electronic health records, but impose strictly sequential generation on trajec…
- arXiv cs.AIresearchStochastic Pruning of the DPO Computation Graph: 1.4x Faster Training and Lower Peak Memory
arXiv:2610.29538v1 Announce Type: cross Abstract: Direct preference optimization (DPO) incurs training costs in output scoring, sequence execution, and backpropagation, so reducing supervision alone does not necessarily…
- arXiv cs.AIagentsThe Reflexivity Threshold: A Phase Transition for Multi-Agent Performative Prediction
arXiv:2610.29577v1 Announce Type: cross Abstract: Many learning systems are performative: once deployed, their predictions change the data distribution on which future models are trained. In multi-agent settings, this fe…
- arXiv cs.AIresearchImproved Training of Strong Stochastic Flow Maps
arXiv:2610.29605v1 Announce Type: cross Abstract: Stochastic flow maps promise few-step sampling of stochastic differential equations (SDEs) by learning to directly jump between times along the solution path, yet trainin…
- arXiv cs.AIresearchOverview of CHIP 2026 Shared Task 1: Patient-Specific Phenotype Concept Recognition in Full-Text Biomedical Literature
arXiv:2610.29606v2 Announce Type: replace-cross Abstract: Automatic phenotype information extraction plays an important role in rare disease diagnosis, genotype-phenotype analysis, and precision medicine. However, accura…
- arXiv cs.AIresearchAn interpretable deep learning method for early hepatocellular carcinoma diagnosis on multiphase CT
arXiv:2610.29616v1 Announce Type: cross Abstract: Early diagnosis of hepatocellular carcinoma is critical to preserve access to curative treatment options. The Liver Imaging Reporting and Data System (LI-RADS) provides a…
- arXiv cs.AIagentsFogTTA: Online Test-Time Adaptation for Robust Transformer-based Object Detection in Foggy Weather
arXiv:2610.29618v1 Announce Type: cross Abstract: Object detection models for autonomous driving commonly experience substantial performance drops when deployed under adverse weather due to the domain shift between train…
- arXiv cs.AIresearchFormalizing Cooperation and Competition: An AI-Assisted Mathematical Addendum to a 2018 Planning Thesis
arXiv:2610.29637v1 Announce Type: cross Abstract: We present an AI-assisted mathematical addendum to Strategic Trip Planning: Striking a Balance Between Competition and Cooperation (Amar, 2018). We reconstruct selected r…
- arXiv cs.AIresearchLineage-Aware Search Control for LLM-Based Evolutionary Factor Mining
arXiv:2610.29663v1 Announce Type: cross Abstract: Formulaic alpha factor mining searches for symbolic expressions that transform market data into predictive signals. Recent LLM-based evolutionary factor mining methods us…
- arXiv cs.AIresearchConflicted Records: Typed Adversarial Contracts for Auditable LLM Output Quality Enforcement
arXiv:2610.29669v1 Announce Type: cross Abstract: LLM-generated records increasingly populate production information systems where they are treated as data assets subject to the same quality expectations as records from…
- arXiv cs.AIagentsToward Recursive Self-Improvement in Physical AI
arXiv:2610.29677v1 Announce Type: cross Abstract: Recursive self-improvement (RSI) describes a system that improves not only its behavior but also the process by which it improves. Recent digital agents test this idea by…
- arXiv cs.AIresearchScaling Multilingual Pretraining of Pixel Language Models
arXiv:2610.29681v1 Announce Type: cross Abstract: Pixel language models process text as rendered images instead of a finite vocabulary, which gives them strong cross-lingual transfer abilities. However, not much is known…
- arXiv cs.AIresearchBio-Inspired Auditory Processing: Coupling Parallel Resonate-and-Fire Dynamics with Ternary Recurrent Networks for Speech Recognition
arXiv:2610.29720v2 Announce Type: replace-cross Abstract: Spiking Neural Networks (SNNs) promise energy-efficient inference through sparse, event-driven computation, yet remain constrained on continuous, context-dependen…
- arXiv cs.AIagentsRetrieval Augmented Generation Compositionality
arXiv:2610.29722v1 Announce Type: cross Abstract: Retrieval Augmented Generation (RAG) grounds large language models in external knowledge. Modern pipelines combine embedding, chunking, retrieval, reranking, query augmen…
- arXiv cs.AIresearchStructure-Aware Message Passing on Petri Nets through Directed Walks and Incidence Diffusion
arXiv:2610.29725v1 Announce Type: cross Abstract: A common application of the process mining discipline is to connect observed event data with Petri nets, which are bipartite, directed graphical process models with rich…
- arXiv cs.AIresearchSAKURA: Serving Attention Key-Value State Under Rate Adaptation for Private Image Editing on Phones
arXiv:2610.29733v1 Announce Type: cross Abstract: Diffusion transformers are widely used in image-editing services. To preserve both efficiency and privacy, existing systems commonly rely on cloud-device collaboration. K…
- arXiv cs.AIresearchMetamodel-Guided LLM Decoding for Consistent DSL Generation
arXiv:2610.29749v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used to generate software engineering artifacts written in domain-specific languages (DSLs). Correct DSL instances usually m…
- arXiv cs.AIresearchWhere Do LLMs Learn to Recommend AI?
arXiv:2610.29785v1 Announce Type: cross Abstract: Asked what to study, which career to pursue, or what product to build, large language models (LLMs) often recommend AI-related options. We ask where this tendency comes f…
- arXiv cs.AIagentsMemoryTax: The Bitter Lesson of Agent Memory
arXiv:2610.29823v1 Announce Type: cross Abstract: Agent memory systems such as Mem0 and Zep decide what to keep before any question arrives; coding agents keep the raw history and let the model search it with its own too…
- arXiv cs.AIresearchRobot Generalization Beyond Volume: The Diversity Path via Zero-Shot Capabilities
arXiv:2610.29829v2 Announce Type: replace-cross Abstract: General-purpose robots must handle tasks, objects and environments they were never trained on, yet zero-shot generalization remains one of the least solved proble…
- arXiv cs.AIresearchS-EDL: Eliciting Self-Evidence from Sequence Likelihoods for Semantic Calibration of LLMs
arXiv:2610.29832v1 Announce Type: cross Abstract: Calibrating large language models (LLMs) in open-ended generation is uniquely challenging because many distinct token sequences can express the same underlying meaning. P…
- arXiv cs.AIresearchBroadband Mid-Wave Infrared Imaging Enabled by All-Silicon Hyperboloid Metalens
arXiv:2610.29841v1 Announce Type: cross Abstract: The mid-wave infrared (MWIR, 3-5 microns) is indispensable for thermal sensing, gas detection, long-range imaging, and free-space optical communications. Meta-optics offe…
- arXiv cs.AIresearchEvery Part Has Its Role: Part-of-Speech Effects in LLM Post-Training
arXiv:2610.29843v1 Announce Type: cross Abstract: Large language models are typically trained with next-token prediction (NTP), which rewards predicting specific tokens rather than explicitly accounting for the semantic…
- arXiv cs.AIagentsPAUSE: Search-Free Steering of Coding Agents Before Their First Source-Code Edit
arXiv:2610.29870v1 Announce Type: cross Abstract: Coding agents can invest substantial effort in repository exploration and testing yet still produce unsuccessful patches. Existing online steering methods review trajecto…
- arXiv cs.AIresearchAutomated Materials Data and Knowledge Extraction using Machine Learning and Large Language Models
arXiv:2610.29895v1 Announce Type: cross Abstract: Over the past decade, substantial efforts have been devoted to developing machine learning (ML) methods for extracting materials data and, where possible, materials knowl…
- arXiv cs.AIresearchAsking a Multimodal LLM Whether Someone Fell: Zero-Shot Screening of Low-Resolution Thermal Video in a Laboratory and an Occupied Home
arXiv:2610.29913v1 Announce Type: cross Abstract: Thermal cameras can watch over older people living alone without capturing faces, and multimodal large language models (LLMs) can judge a short video without task-specifi…
- arXiv cs.AIresearchUnintended Side Effects of Value Training in LLMs
arXiv:2610.29922v1 Announce Type: cross Abstract: As LLMs are increasingly deployed in value-sensitive contexts, aligning them with human values has emerged as a post-training objective in NLP, aimed at instilling additi…
- arXiv cs.AIresearchPrivacy in Context Is Being Overlooked in the Age of General-Purpose LLMs
arXiv:2610.29925v1 Announce Type: cross Abstract: As large language models (LLMs) continue to grow in scope and capability, privacy concerns are on the rise. Since users increasingly interact with a single general-purpos…
- arXiv cs.AIresearchYour Benchmark Is an Empirical Measure Over Difficulty
arXiv:2610.29927v1 Announce Type: cross Abstract: A benchmark is not merely a collection of test questions; it naturally induces an empirical measure over difficulty. In this work, we develop this measure-based view of b…
- arXiv cs.AIresearchGraph Topology Meets Energy-Driven Pathfinding: Preserving Contextual Consistency in Retrieval-Augmented Generation
arXiv:2610.29933v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) frequently integrates knowledge graphs (KGs) for complex multi-hop question answering. However, their performance is increasingly bot…
- arXiv cs.AIresearchCulturalRiddles: A Multicultural Benchmark of Riddles
arXiv:2610.29968v3 Announce Type: replace-cross Abstract: As LLMs expand their language coverage, evaluating how well they understand and represent diverse cultures becomes increasingly important. However, many benchmark…
- arXiv cs.AIagentsFaultGene: LLM-Assisted Fault-Augmented Test Generation for Hardware-in-the-Loop Validation of Autonomous Driving Systems
arXiv:2610.29969v1 Announce Type: cross Abstract: Reliable validation of autonomous driving cyber-physical systems requires testing not only nominal driving behavior but also failures arising from faults in sensing and e…
- arXiv cs.AIresearchHiddenLens: A Multi-Layer LLM Framework for Detecting and Resolving Hidden Assumptions in Software Requirements
arXiv:2610.29996v1 Announce Type: cross Abstract: Natural-language software requirements often omit assumptions about performance, operating conditions, user behaviour, and domain constraints, affecting architecture, tes…
- arXiv cs.AIresearchEvery Alarm Has a Cause: An Open Generator of Telecom Alarm Storms with Exact Root Causes, Bound to NORIA-O, RFC 8632 and TMF642
arXiv:2610.30004v1 Announce Type: cross Abstract: Alarm root-cause analysis is studied on data that cannot be shared. Operator logs are confidential, so what the field publishes is a causal graph between alarm types rath…
- arXiv cs.AIresearchBuilding Auditable AI Text Detectors with Sparse Autoencoders
arXiv:2610.30006v1 Announce Type: cross Abstract: AI-generated text detectors are increasingly deployed in consequential settings---peer review, education, admissions, journalism, and content moderation---where their out…
- arXiv cs.AIagentsAgent Behavior Maps: Locating Agents by What They Would Do, Without Running Them
arXiv:2610.30014v1 Announce Type: cross Abstract: LLM agents with similar success rates can follow different action sequences. An Agent Behavior Map represents LLM-harness combinations using centered action log-likelihoo…
- arXiv cs.AIresearchCode Comprehensor: Hierarchical Documentation and Cross-Modal Retrieval for Large Repositories
arXiv:2610.30016v2 Announce Type: replace-cross Abstract: Understanding large, complex, and rapidly evolving code bases remains a core challenge for software engineering at scale, hindering onboarding, maintenance, refac…
- arXiv cs.AIresearchStationarity Constraints Improve Both Energies and Densities of Machine-Learned Exchange-Correlation Functionals
arXiv:2610.30022v1 Announce Type: cross Abstract: Empirical exchange-correlation functionals are fitted on fixed orbitals but used self-consistently, so better energies often come with worse densities. We show that the B…