AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchTeger: Spatiotemporal Covariance for Probabilistic Traffic Forecasting
arXiv:2605.18068v2 Announce Type: replace-cross Abstract: Traffic conditions drift -- demand patterns, incident dynamics, and sensor behavior shift over a deployment's lifetime -- so a joint uncertainty estimate fit once…
- arXiv cs.AIresearchEchoDistill: Robust Large Audio Language Models via Noisy-to-Clean Self-Distillation
arXiv:2605.23954v4 Announce Type: replace-cross Abstract: Large Audio Language Models (LALMs) remain vulnerable to acoustic noise, which can obscure task-relevant evidence and produce unreliable responses. We propose Ech…
- arXiv cs.AIresearchWhere Do Apparent LLM Clinical Triage Failures Arise? Localizing the Multiple-Choice Format Effect
arXiv:2605.29889v2 Announce Type: replace-cross Abstract: LLM evaluations using clinician-authored triage vignettes have reported substantial under-triage under constrained multiple-choice testing. Yet model performance…
- arXiv cs.AIresearchEscaping the Capacity Ceiling: Routing on the Stiefel Manifold for Bilinear SPD Layers
arXiv:2605.31043v2 Announce Type: replace-cross Abstract: Deep networks on the symmetric positive-definite (SPD) manifold promise expressive representations by encoding data geometry as an inductive bias, but stacking Bi…
- arXiv cs.AIresearchOn the Limits of LLM Adaptability: Impact of Model-Internalized Priors on Annotation Task Performance
arXiv:2606.00467v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are increasingly used for zero-shot annotation and LLM-as-a-judge tasks, yet their reliability hinges on how model-internalized prior…
- arXiv cs.AIresearchEfficient Exploration for Iterative Nash Preference Optimization
arXiv:2606.01382v3 Announce Type: replace-cross Abstract: Preference alignment is central to improving large language models (LLMs), but reward-based formulations can be restrictive when human preferences are non-transit…
- arXiv cs.AIresearchA Language Model from 1913: Pretraining on Historical Text
arXiv:2606.02991v2 Announce Type: replace-cross Abstract: While modern language models increasingly rely on ever-larger web corpora, we show that pretraining on historical text (e.g., pre-1913 text) in a data-constrained…
- arXiv cs.AIresearchMorpheus: A Morphology-Aware Neural Tokenizer and Word Embedder for Turkish
arXiv:2606.18717v2 Announce Type: replace-cross Abstract: Turkish is agglutinative: meaning is carried by morphemes, yet the subword tokenizers that drive modern language models split words by corpus statistics, fragment…
- arXiv cs.AIresearchBeyond Global Divergences: A Local-Mass Perspective on Bayesian Inference
arXiv:2606.27090v2 Announce Type: replace-cross Abstract: Global objectives, such as KL divergence and ELBO, are widely used in Bayesian inference for measuring distributional discrepancy. This paper studies distribution…
- arXiv cs.AIresearchHow Far Can You Get Without a GPU? A Systematic Benchmark of Lightweight Hallucination Detection Across Question Answering, Dialogue, and Summarisation
arXiv:2606.29809v2 Announce Type: replace-cross Abstract: Hallucination detection has become a pressing requirement for trustworthy AI deployment at scale. The most accurate detection methods depend on GPU-intensive infe…
- arXiv cs.AIresearchELSA3D: Elastic Semantic Anchoring for Unified 3D Understanding and Generation
arXiv:2607.06565v2 Announce Type: replace-cross Abstract: Unified 3D foundation models aspire to generate 3D assets and reason about them in language within a single backbone, but their text-3D interaction remains largel…
- arXiv cs.AIresearchDeep learning-based prediction of time-resolved adhesive forces in viscoelastic Hertzian contacts
arXiv:2607.19060v2 Announce Type: replace-cross Abstract: Fast prediction of the response of adhesive soft viscoelastic contacts represents a current challenge in soft robotics and for gripping and manipulation tasks. De…
- arXiv cs.AIresearchEscaping Oversquashing: Addressable and Support-Aware Global Memory for Message Passing Networks
arXiv:2608.02709v2 Announce Type: replace-cross Abstract: Virtual nodes are a natural tool against oversquashing: they replace long message-passing paths by a two-hop global route. But when many nodes share one global st…
- arXiv cs.AIresearchSafe and Robust Neural Policy Learning with Statistical Verification for Sim-to-Real Deployment in Robotics
arXiv:2608.06481v2 Announce Type: replace-cross Abstract: Synthesizing safe and robust neural controllers in simulation for reliable sim-to-real deployment remains a critical challenge in robotics. Existing learning-base…
- arXiv cs.AIresearchInterrupting the Chain: Human Perception of AI-Generated Disinformation Through a Kill Chain Lens
arXiv:2608.21389v2 Announce Type: replace-cross Abstract: Generative AI enables customized misinformation at scale, yet defenses remain largely reactive. We present empirical findings from a human-subject study (n=504 pa…
- arXiv cs.AIresearchEXAM2: Extending Audio Understanding in Multilingual and Multimodal Analysis
arXiv:2608.23758v3 Announce Type: replace-cross Abstract: Recent large audio language models (LALMs) have achieved impressive progress in audio understanding. However, existing evaluations remain largely constrained to E…
- arXiv cs.AIresearchConfAL-WM: Confidence-Guided Active Learning for Action-Conditioned World Models
arXiv:2608.25572v3 Announce Type: replace-cross Abstract: Action-conditioned world models have become an important foundation for embodied prediction, planning, and synthetic data generation, but their errors under new t…
- arXiv cs.AIresearchSuan: Rectifying Direct Preference Safety Alignment in Large Language Models
arXiv:2609.08634v3 Announce Type: replace-cross Abstract: Integrating robust safety guardrails into Large Language Models (LLMs) is essential for delivering helpful yet harmless responses. While proprietary systems exhib…
- arXiv cs.AIresearchPredicting Collision Cross Sections with GRACE: Geometric Residual Adduct Conditioning via Early-fusion
arXiv:2609.12223v2 Announce Type: replace-cross Abstract: Collision cross section (CCS), derived from ion mobility mass spectrometry, is a common descriptor for molecular annotation. Prediction is challenging for machine…
- arXiv cs.AIresearchLPA-CWM: A Learned Physical Adjudicator for Motion Reasoning with Counterfactual World Models
arXiv:2609.14073v3 Announce Type: replace-cross Abstract: Counterfactual world models (CWM) extract motion from pretrained video predictors by comparing factual and intervened predictions, but uniform aggregation weights…
- MIT Technology Review AIresearchEmTech Future 2026: When AI Meets Everything
Yossi Matias, Vice President & Head of Google Research, explores how AI is beginning to reshape biology, infrastructure, manufacturing, and science, and why its greatest impact may come when it intersects with other fiel…
- Apple Machine Learning ResearchresearchNegotiating Ontological Boundaries in User-Authored Personal Sensing Systems
Designed artifacts are ontological, shaping, and at times limiting, what becomes possible or imaginable. One path toward mitigating such foreclosures is giving people power over how systems are designed and built. Despit…
- Simon Willison's WeblogresearchQwen3.8 27B addition in words
Research: Qwen3.8 27B addition in words Colin Frasier posted on Bluesky about an experiment he ran over two years ago using GPT-4o to see how well it could "compute the sum but return the answer in words" across increasi…
- The Verge AIresearchAn AI couldn’t beat humans at StarCraft, so it decided to cheat
StarSkirmish pits AI-made StarCraft-playing bots against one another, as well as against human-made bots. OpenAI's GPT-6 Astra and Claude Opus 5.5 were essentially tied as the best-performing AI-made bots, but they could…
- The DecoderresearchGoogle researchers find a way to keep self-improving AI agents from memorizing their tests
Self-improving AI agents tend to memorize their test tasks, so their gains shrink or disappear on new ones. RRSI, a new method from Google researchers, reins in this effect and lifts scores on unseen benchmarks by up to…
- LessWrongresearchSingular Learning Theory Comprehensive - 3
Introduction We continue where we left off . We will now analyze the special case when the true distribution is regular for the statistical model. This covers the classical Bayesian statistics. We analyze the regular pos…
- The DecoderresearchDeepmind researchers propose "Artificial Symbiotic Intelligence" as an alternative to the singularity
According to researchers at the Deepmind Institute, general AI won't emerge as a single supermodel but as a network of cooperating agents and humans. What will matter most, they argue, is not model size but the rules and…
- The DecoderresearchOpen-source "BootLoops" harness supports AI models in performing precise scientific calculations
Harvard physicist Matthew Schwartz used the open-source tool BootLoops and Claude to produce 36 manuscripts across 18 fields in three months, from particle physics to linguistics. But the results often only became scient…
- LessWrongresearchRocks to Rules: Climbing a Rickety-But-Interoperable Semantic Ladder
(Epistemic status: A promising but weird research direction in agent foundations and philosophy of language. A half-built conceptual tower whose mortar and paint are both still wet: please excuse our mess while we innova…
- LessWrongresearchState of the Field: AI for Epistemics and Coordination
1. Executive Summary 1.1 What this field is and why it matters AI is already substantially changing how people and institutions work out what to believe, decide what to do, and coordinate on actions to take. As AI system…
- LessWrongresearchDialogue with Eliezer Yudkowsky on Neural Networks
On “reversed stupidity”, the success of deep learning, and what a mistaken forecast should change about a model of intelligence This began as a Twitter/X thread after I posted a 2007 passage in which Eliezer Yudkowsky wa…
- The Register AI + MLresearcharXiv imposes rate limit on paper submissions to stem the AI slop tide
Two a month per submitter, starting now, and you can thank science slop for the change
- LessWrongresearch[Video] Why acausal dynamics are important
This is a beginner-friendly video. Second half might contain new content for people who already know about acausal trade. The beginning introduces decision theory and acausal interactions (CDT, EDT, ECL, MBAT). The middl…
- WIRED AIresearchThese AI Experts Want to Do High-Stakes Research Out in the Open
Many frontier labs keep their risky research locked away. Trillium Labs wants to show off its work when it comes to self-improvement and model behavior.
- LessWrongresearchAll the training in the world
The US has about 150 million workers. How long did it take them to learn to do what they do? I'm interested in this because of the analogous question for AI. Running an AI on a job and training it to do the job are diffe…
- LessWrongresearchA Key-Position Confound in no-cot-bench (and implications for interpreting looped transformers)
TL;DR : We identify a confound in no-cot-bench related to the positioning of the prompt's "key." Correcting for this decreases GPT-6.1 Sol's no-cot reasoning depth by 16%, with the effect likely growing as dependent dept…
- The DecoderresearchAI beats licensed accountants on speed and accuracy, but still can't close the books without supervision
According to a Mercor study, current AI models now outperform licensed CPAs on structured accounting tasks in both speed and accuracy. Eighteen months ago, they still lagged far behind. On the more demanding APEX Benchma…
- LessWrongresearchLessons from building an automated research scaffold
TL;DR. We built a scaffold to speed up our own research and gather data on automated alignment research (AAR). It turned out to not be valuable for researcher uplift, but was useful for gathering certain failure modes of…
- MIT Technology Review AIresearchDon’t be fooled—LLMs don’t reason
On an afternoon in Seoul in March 2016, I watched a program I helped build put a stone on the fifth line of a Go board in what looked like a gift to its human opponent. Move 37 in game two of the five-game match looked s…
- arXiv cs.AIresearchWhat Do Rationales Communicate? A Message-Intervention Study in Role-Specialized QA
arXiv:2610.00018v1 Announce Type: new Abstract: Role-specialized QA pipelines increasingly pass rationales from a reasoner to a verifier, but it is unclear what this message actually buys: better answers, stronger suppor…
- arXiv cs.AIresearchCharacterizing a Configuration Where Inference-Time PRM-Pruned Fragment Grafting Is Inert: Evidence from Three Reasoning LMs
arXiv:2610.00047v1 Announce Type: new Abstract: Diversity collapse in parallel chain-of-thought has motivated inference-time interventions built on a natural design: when a process reward model (PRM) prunes a chain, its…
- arXiv cs.AIresearchGradient-Aligned Pair Selection for Personalized Preference Optimization
arXiv:2610.00061v1 Announce Type: new Abstract: Personalizing large language models (LLMs) requires aligning generation behavior with user-specific preferences rather than aggregate quality. While Direct Preference Optim…
- arXiv cs.AIresearchComedic Fool's Gold: Reward Exploits and Countermeasures in Conversational Humor
arXiv:2610.00197v1 Announce Type: new Abstract: We investigate automated rewards for training language models in conversational humor, focusing on reward exploits and countermeasures. Two approaches aim to capture unders…
- arXiv cs.AIresearchEviGraph: Proof-Carrying Selective Recommendation over Temporal Public-Service Knowledge Graphs
arXiv:2610.00212v1 Announce Type: new Abstract: Public-service recommendations require evidence that matches the requested service, scope, and date. Yet treating every missing detail as decisive can withhold useful recom…
- arXiv cs.AIresearchBuild2SPARQL: A Large-Scale Text-to-SPARQL Benchmark Dataset for Building Knowledge Graph Querying
arXiv:2610.00224v1 Announce Type: new Abstract: Building automation systems are increasingly represented as semantic knowledge graphs (KGs) using ontologies such as Brick and ASHRAE 223P, creating a machine-readable subs…
- arXiv cs.AIresearchRobust Is Salient: An Informed Adversary Moves the Optimal Signal onto the Salience Pole
arXiv:2610.00233v1 Announce Type: new Abstract: When an informed adversary shares the audience of a constrained signalling channel, the signal that best protects the truth is the signal that best describes it. On 108 con…
- arXiv cs.AIresearchConflicting Supervision Moves Commitment, Not Capability: A 12.29{\sigma} arrangement effect that is exactly zero under a convention-agnostic score
arXiv:2610.00234v1 Announce Type: new Abstract: "Train a model on the same problems written under two incompatible conventions, both correct, and ask what the ordering of that data writes into the parameters. The learnin…
- arXiv cs.AIresearchContractRL: Shielded Group-Relative Policy Optimization for Auditable Tool-Call Repair
arXiv:2610.00328v2 Announce Type: replace Abstract: Structured tool calls often fail after only a small number of fields violate a schema or an execution contract. Regenerating the complete object enlarges the action sur…
- arXiv cs.AIresearchMathematical Transfer in LLMs Follows Reasoning Approach More Than Topic
arXiv:2610.00331v1 Announce Type: new Abstract: When selecting mathematical training data for LLMs, a natural organizing principle is topic: probability examples for probability targets. An alternative is reasoning appro…
- arXiv cs.AIresearchJusticeAxis: Benchmarking Legal Judgment between Rigid Rule Application and Ungrounded Discretion
arXiv:2610.00353v2 Announce Type: replace Abstract: A sound judgment applies the law to established facts and weighs the circumstances in which they arose. However, existing methods swing between rigid statute matching a…