AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchMimir: A Sub-2B Hierarchical Reasoning Model Trained on Permissible Data Punches Above Its Weight Class
arXiv:2608.13517v3 Announce Type: replace-cross Abstract: Training capable language models typically relies on web-scale pretraining followed by multi-stage post-training, creating substantial computational and data-gove…
- arXiv cs.AIresearchInterrupting the Loop: Periodic Subject Changes Raise Judged Surprise and Connection in Base Language Models
arXiv:2608.19893v2 Announce Type: replace-cross Abstract: Where does the novelty a base language model produces with no task come from, and what can an LLM judge of a long stream actually see? We dismantle a cognitively…
- arXiv cs.AIresearchMoving the Mean Toward the Known Good, Not Beyond It: What Inference-Time Interventions and Weight Consolidation Buy in Open-Ended Generation
arXiv:2608.28886v2 Announce Type: replace-cross Abstract: What does a generation loop gain from learning on its own verified successes? In cycles of generate, verify, select and LoRA-consolidate on online bin packing, tr…
- arXiv cs.AIresearchFluxVLA Engine: A One-Stop VLA Engineering Platform for Embodied Intelligence
arXiv:2609.17210v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models, world-action models (WAMs), and offline reinforcement learning methods are rapidly expanding the design space of embodied pol…
- TechCrunch AIresearchLeft alone with nothing to do, AI agents started playing
MIT researchers marooned 13 AIs on a virtual island, and they responded by inventing games, mourning a lost ring and, eventually, getting better at their jobs.
- LessWrongresearchWah wah wah wah do more AI R&D
Ice cream There's a particular kind of listening that kids (and adults) sometimes do. Daddy is saying stuff—his mouth is moving and making noise—and he's talking about what I ate for lunch, and something about other time…
- The Register AI + MLresearchHuman receives AI-designed virus for the first time
Not to kill the human, of course – to kill the antibiotic-resistant bacteria causing their infection
- MIT Technology Review AIresearchThe Foundations of Scalable AI
A scalable AI system requires a strong foundation. Data, engineering, platforms, operating models, and governance must converge to work as one. This session from MIT Technology Review’s EmTech Future conference explores…
- TechCrunch AIresearchMicrosoft’s Mustafa Suleyman says its AI outperforms doctors on hard cases as he chases ‘medical superintelligence’
Microsoft’s new AI diagnostic system beat generalist doctors on hard cases, according to a study in Science. But most of the improvement seems to come from the AI models underneath, not from Microsoft’s system itself.
- LessWrongresearchOpening up Attention: A QK Transcoder Dashboard for Feature Pairs
Multi Head Attention in Transformers continues to be an elusive topic in mechanistic interpretability. One way of trying to decompose MHA into interpretable parts is applying SDL (Sparse Dictionary Learning) methods to t…
- Simon Willison's WeblogresearchQuoting Armin Ronacher
As fun as AI is, we built so much bad software over the last 30 years, and now the universe is punishing us for our sins. — Armin Ronacher Tags: security , generative-ai , armin-ronacher , ai , ai-security-research , llm…
- The DecoderresearchRecursive shows first result of its AI-driven research process with Flint
The AI startup Recursive is unveiling Flint, its first language model, a 40-billion-parameter MoE for local coding developed by former DeepMind researchers. It was created in four months using the company's in-house AI s…
- LessWrongresearchMonitorability evaluations and policy proposals
There has been a lot of discussion recently of policy proposals around monitorability, such as Redwood's proposal and my counter-proposal . I'd like to say a bit more generally about how I'm thinking about monitorability…
- LessWrongresearchThe Relief Paradox: How We Let AI 'Undermine Our Autonomy'
“Users are often active participants in the undermining of their own autonomy…” - Anthropic, January 28, 2026 The Unanswered Conflict Anthropic’s study on disempowerment [1] identified a confusing paradox: in conversatio…
- IEEE Spectrum AIresearchWhy Engineers Should Brave Capitol Hill
When San Antonio–based software engineer Nikhil Jathar first went to Washington, D.C., to advocate for federal support for technology education and research funding, he was in awe of the opportunity. It was spring of 202…
- The Verge AIresearchClaude did not invent scorpion antivenom
An investment research firm wanted to prove AI could revolutionize drug development. So they teamed up with Anthropic to see whether an unreleased version of Claude could make scorpion antivenom. It couldn't. It came up…
- WIRED AIresearchHugging Face’s New AI Biology Model Lets You Chat With DNA
The new open-source model speaks the language of DNA and can help researchers understand the effects of any changes on gene activity and health.
- Ai2 BlogresearchA crop-mapping benchmark for the tropics
PLANTEUR extends the PASTIS crop-mapping benchmark to six tropical regions to help evaluate geospatial models across more diverse agricultural systems.
- NVIDIA BlogresearchNVIDIA Cosmos Opens New Tools to Train, Evaluate and Deploy World Models
To help developers rapidly build world models, which help physical AI systems understand and simulate the real world, NVIDIA has expanded the Cosmos platform with new training tools, simulation checkpoints and Cosmos Dat…
- NVIDIA BlogresearchNVIDIA Open Models Power a New Wave of European Public Sector Projects
Governments need modern solutions to serve the public while keeping sensitive information under their control. Open models provide a path forward, letting governments evaluate them, adapt them to local languages and publ…
- arXiv cs.AIresearchA Small Model Asks Better: Fine-Tuning Query Clarification for Retrieval-Augmented Generation
arXiv:2610.28686v1 Announce Type: new Abstract: Query clarification is essential for retrieval-augmented generation (RAG) systems that face ambiguous user queries. We consider multi-turn grounded conversational scenarios…
- arXiv cs.AIresearchSpecEvo: Speculative Evolution with Large Language Models for Cost-Efficient Scientific Discovery
arXiv:2610.28706v1 Announce Type: new Abstract: LLM-driven evolutionary search is a promising paradigm for scientific discovery, but existing methods remain costly and slow, often applying expensive reasoning uniformly w…
- arXiv cs.AIresearchDecision language models as affordable and rapid alternatives to LLM judges of clinical generative AI
arXiv:2610.28826v1 Announce Type: new Abstract: Automated judges of clinical artificial intelligence (AI) outputs are necessary, but large language model (LLM) judges are costly and slow at scale. We compared Jev, a deci…
- arXiv cs.AIresearchSketch2Sim: an end-to-end modular framework for hand-drawn circuit analysis
arXiv:2610.28836v1 Announce Type: new Abstract: This study proposes a sketch-to-simulation system to solve handwritten circuit diagrams. The system converts raw images into a Simulation Program with Integrated Circuit Em…
- arXiv cs.AIresearchSpeedrunning Relational Foundation Model Pretraining
arXiv:2610.28855v1 Announce Type: new Abstract: Progress on foundation model pretraining is gated by who can afford a trial, and relational pretraining is no exception. Recipes are developed inside individual labs, repor…
- arXiv cs.AIresearchTo Manipulate or Not: Opinion Dynamics in LLM Interactions
arXiv:2610.28875v1 Announce Type: new Abstract: Large language models increasingly take part in extended conversations where they can both shape and be shaped by another party's views, yet most persuasion research measur…
- arXiv cs.AIresearchDiffResearch: Accelerating Deep Research with Diffusion Language Models
arXiv:2610.28909v1 Announce Type: new Abstract: Deep research systems iteratively plan, gather evidence, synthesize, and revise, making end-to-end latency a key bottleneck for interactive use. Almost all production syste…
- arXiv cs.AIresearchSimply Logical -- The First Three Decades
arXiv:2610.28912v1 Announce Type: new Abstract: This paper charts the evolution of the Prolog textbook Simply Logical -- Intelligent Reasoning by Example from print with runnable programmes on a 3.5-inch diskette publish…
- arXiv cs.AIresearchGRAIL: From Saliency to Semantics in Time-Series Explanation
arXiv:2610.29036v1 Announce Type: new Abstract: Explaining a time-series model requires both locating the evidence and extracting meaningful knowledge from it. Yet a single timestep is not a semantic unit: the meaningful…
- arXiv cs.AIresearchAutoFraming: Synthesizing Dynamic Frames of C Code with LLMs
arXiv:2610.29046v1 Announce Type: new Abstract: Large language models (LLMs) have shown considerable promise in synthesizing formal specifications from source code. However, existing approaches primarily focus on functio…
- arXiv cs.AIresearchDoes Every Instance Count Equally? Order Effects in LLM Multi-Instance Processing
arXiv:2610.29057v1 Announce Type: new Abstract: Users increasingly rely on large language models (LLMs) to analyse collections of independent inputs, such as product reviews or social media posts, and return a single agg…
- arXiv cs.AIresearchContext-Augmented, Session-Calibrated Blood Pressure Tracking from Photoplethysmography
arXiv:2610.29091v1 Announce Type: new Abstract: Objective.To distinguish the contributions of acquisition context and photoplethysmography (PPG) to session-calibrated blood pressure (BP) tracking.Approach. The original c…
- arXiv cs.AIresearchSame Answer, Different Reasons: Trace-Level Divergence in Multilingual Large Language Models
arXiv:2610.29092v1 Announce Type: new Abstract: Multilingual large language models are increasingly deployed in settings where visible reasoning traces support verification, education, and safety auditing, yet standard e…
- arXiv cs.AIresearchGRAM: Group-wise Rank-Aware Model Merging via Subspace Alignment
arXiv:2610.29110v1 Announce Type: new Abstract: Merging different models into a single model is highly desirable for multi-task deployment, particularly in regulated domains like healthcare. In such settings, models are…
- arXiv cs.AIresearchStochIKM: Automated High-Fidelity Reconstruction of Individual Patient Data from Published Kaplan-Meier Curves
arXiv:2610.29122v2 Announce Type: replace Abstract: Individual patient data are the gold standard for secondary analysis of time-to-event evidence, but they are rarely released, and reconstruction from a published Kaplan…
- arXiv cs.AIresearchNormTune: Norm-Guided Parameter-Efficient Fine-Tuning for Reasoning-Intensive Tasks
arXiv:2610.29134v1 Announce Type: new Abstract: Full fine-tuning has achieved remarkable success on reasoning-intensive tasks, but it often requires substantial GPU resource consumption. Parameter-efficient fine-tuning (…
- arXiv cs.AIresearchTeachBack: Learning to Teach via Bidirectional Preference Optimization for On-Policy Self-Distillation
arXiv:2610.29167v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) enables a language model to learn from a Teacher instantiated from the same model but given access to privileged information, such as a r…
- arXiv cs.AIresearchWhen Multiple Choices Are Correct: Asymmetric Probability Allocation in Jev and Other Decision Models
arXiv:2610.29217v1 Announce Type: new Abstract: Decision models return normalized probability distributions over candidate choices, which downstream applications can use to select among choices. Although their providers…
- arXiv cs.AIresearchFrom Scores to Safe Sets: Exact Safety--Constrained Decoding for Medication Recommendation
arXiv:2610.29228v1 Announce Type: new Abstract: Recent generative medication recommendation systems ultimately produce sets of drugs, but drug--drug interaction (DDI) constraints depend on the set as a whole. A natural p…
- arXiv cs.AIresearchARCANA: A Benchmark for Abstraction and Analogical Reasoning
arXiv:2610.29271v3 Announce Type: replace Abstract: Analogical reasoning is widely considered a fundamental component of human intelligence. Few benchmarks are designed to explicitly test far analogical reasoning - reaso…
- arXiv cs.AIresearchSame Probabilities, Different Advice: Gain-Loss Framing Effects in High-Stakes LLM Decision Support
arXiv:2610.29294v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to support consequential decisions, yet their reliability under equivalent representations of uncertainty remains unclear…
- arXiv cs.AIresearchLLM-Based Exogenous World Modeling for Dynamic Scheduling
arXiv:2610.29308v1 Announce Type: new Abstract: Dynamic scheduling requires dispatching online arrivals while anticipating future jobs, as poor decisions can compound downstream costs under nonlinear tardiness objectives…
- arXiv cs.AIresearchSpatialBrain: Spatial Intelligence Growing from Experience
arXiv:2610.29317v1 Announce Type: new Abstract: Spatial reasoning requires more than access to geometric tools: a reasoner must decide when direct observation is sufficient and when to reconstruct, measure, or change ref…
- arXiv cs.AIresearchSolving Go under Positional Superko: Sound Proof Transfer and New Board Values
arXiv:2610.29414v1 Announce Type: new Abstract: Positional superko (PSK) forbids recreating any earlier whole-board position. It is part of the Chinese rules as written and of the rules used in computer Go. Yet almost al…
- arXiv cs.AIresearchMERP: A Latent-Bottleneck Framework for Robust Multi-Modal Multi-Label Emotion Recognition
arXiv:2610.29430v1 Announce Type: new Abstract: Multimodal multi-label emotion recognition is important for affect-aware systems, but models trained with complete text, visual, and acoustic streams often degrade sharply…
- arXiv cs.AIresearchEvents, Not Pixels: Where World Models Get the Return Wrong
arXiv:2610.29435v1 Announce Type: new Abstract: World models are increasingly used for planning, where a planner ranks candidate actions by returns imagined by the model. However, these models are judged mainly by how we…
- arXiv cs.AIresearchRubricOpt: Self-Revision of Semantic Rubrics for Preference Optimization
arXiv:2610.29491v1 Announce Type: new Abstract: A model's failures can reveal gaps in the behavioral criteria guiding its training. We introduce RubricOpt, a framework that lets a policy revise these criteria within pref…
- arXiv cs.AIresearchAn Exact 93-Move Solution to a Nonlocal Crystal-Exchange Puzzle
arXiv:2610.29493v1 Announce Type: new Abstract: We determine the minimum number of directional commands needed to solve alevel of Order of the Sinking Star, modeled as a crystal-exchangepuzzle on an 11*11 board. A comman…
- arXiv cs.AIresearchParallel Thinking for Large Language Model with Path Diversity
arXiv:2610.29501v1 Announce Type: new Abstract: Parallel thinking has emerged as a promising paradigm for enhancing the reasoning capabilities of Large Language Models (LLMs) by exploring multiple reasoning paths simulta…
- arXiv cs.AIresearchFrom Association to Decision Value: Testing Paired Instruction Dependence for VLA Corpus Selection
arXiv:2610.29646v1 Announce Type: new Abstract: Choosing among robot demonstration corpora is a ranking problem: an upstream diagnostic must preserve which candidates produce better downstream policies, not merely correl…