AI news archive.
10,659 articles filed under Research, newest first, from the outlets listed on the sources page.
- arXiv cs.AIresearchD$^3$-MOPD: Dynamic Domain ScheDuling for Efficient Multi-Teacher Distillation
arXiv:2608.24987v2 Announce Type: replace-cross Abstract: Multi-teacher on-policy distillation (MOPD) distills several domain-expert teachers into a single student by minimizing per-domain reverse-KL divergence on the st…
- arXiv cs.AIresearchCurvature Cryptanalysis of Smooth Transformer Feed-Forward Networks
arXiv:2608.28843v2 Announce Type: replace-cross Abstract: We show that smooth two-layer feed-forward networks (FFNs) expose an additional structural model extraction channel under a chosen-input raw-output oracle at the…
- arXiv cs.AIresearchVerify Before You Distill: Prompt-Level Teacher Gating for On-Policy Distillation
arXiv:2609.02998v2 Announce Type: replace-cross Abstract: On-policy distillation (OPD) accelerates post-training by providing dense token-level supervision from a frozen teacher on the student's own rollouts. Vanilla OPD…
- arXiv cs.AIresearchSparse Data Augmentation for Optimization with Provable Guarantees
arXiv:2609.08133v2 Announce Type: replace-cross Abstract: In nonconvex optimization problems arising in geometric machine learning, data augmentation is commonly used to promote invariance by averaging empirical losses o…
- arXiv cs.AIresearchUFO: Chain-of-Evaluation for Omni-Condition Alignment in Multi-Modal Image Generation
arXiv:2609.12397v2 Announce Type: replace-cross Abstract: Multi-modal image generation, particularly subject-driven customization, has garnered growing attention in recent years. Despite the rapid advancement of generati…
- arXiv cs.AIresearchAn Efficient and Modular Framework for Targeted Harm Mitigation in LLMS
arXiv:2609.13624v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are powerful zero-shot learners but remain prone to misalignment with human preferences, often producing biased, toxic, or otherwise…
- arXiv cs.AIresearchLegislating World-Model-Based Planning with Legal Reasoning
arXiv:2609.15113v3 Announce Type: replace-cross Abstract: As robotic systems grow more general, legal norms are needed to integrate them into society. This paper extends the isomorphism problem of aligning legal source t…
- arXiv cs.AIresearchWebCraftBench: Evaluating Web Application Generation from a Software Testing Perspective
arXiv:2609.15387v3 Announce Type: replace-cross Abstract: Human evaluation provides a direct measure of the quality of LLM-generated web applications. However, fitting human judgments through automated evaluation remains…
- arXiv cs.AIresearchHow Humans and LLMs Read Gender into "Gender-Neutral" Physical Descriptions
arXiv:2609.16366v2 Announce Type: replace-cross Abstract: When foundation models describe people, recent work in AI fairness, accessibility, and ethics recommends avoiding inferred identity labels (e.g., "she", "his") in…
- Engadget AIresearchAnthropic has set up a bio research lab for physical experiments
Anthropic now has its own bio research lab in San Francisco.
- Apple Machine Learning ResearchresearchDynamically Scaled Activation Steering
Activation steering has emerged as a powerful method for guiding the behavior of generative models towards desired outcomes such as toxicity mitigation. However, most existing methods apply interventions uniformly across…
- LessWrongresearchWhat is (and isn’t) gained by avoiding architectures with high opaque serial depth?
Here , we’ve given an operationalization of opaque serial depth, a metric designed to be a good (albeit imperfect) proxy for the amount of opaque serial cognition that models can perform. While maintaining low opaque ser…
- TechCrunch AIresearchGoogle DeepMind launches institute to widen the AGI debate
The new institute aims to surface differing views between Google, Google DeepMind, and the broader global research community around AGI. "They will not always agree, and they will likely change their minds, as more data…
- BBC TechnologyresearchThe virtual worlds where robots are trained
Training systems that allow robots to negotiate the real world are getting more sophisticated.
- LessWrongresearchThe J-lens offset is the model's token frequency: z-scoring helps
This is a linkpost for the write-up on my site ; the full body is below, and the code, decisions ledger and devlog are in the repo . Base-model z-score calibration of the J-lens helps elicit hidden secret words from Cywi…
- The Verge AIresearchFlash floods can strike without warning — this new technology could change that
On the morning of June 9th, Laura Lin was working from her home in Lanesville, a rural southern Indiana town about 15 miles from the Kentucky border. She was on a Zoom call, unaware that the heavy rain outside was beginn…
- LessWrongresearchSwarm Organization as the Exponent on Test-Time Compute
Swarm organization - the efficacy of cooperation between AIs in a multi-agent system - may change how parallel test-time compute increases AI capabilities, moving it from a sublinear [1] to a superlinear exponent. [2] Th…
- The Register AI + MLresearchScientific papers become agentic chatbots with new tool
Why go through the hassle of reading a study for yourself when you can turn it into an AI agent and tell it to reproduce the analysis for you?
- AI Stack ExchangeresearchWhy AI cannot develop mathematical theories?
At present, AI is good at solving specific mathematical problems, but not at developing new mathematical theories and concepts. Yet everyone says we cannot rule out the possibility that this will change in the future. Wh…
- The Verge AIresearchAI is feared globally as the destroyer of jobs
Pew Research has published a new global survey that sheds light on how people view AI, including its impact on jobs, life in general, and income inequality. The survey questioned 42,151 people across 37 countries from Fe…
- AI Stack ExchangeresearchAre AI alignment problems universally noncomputable?
Since it is in the news, I wanted to find out more about the AI alignment and suspected it is not Turing computable similar to the Halting problem. I was able to find a recent reference that claims to prove that AI inner…
- Ai2 BlogresearchWhat a crowdsourced game revealed about steering Olmo 3
A crowdsourced game built on Olmo 3 showed how people can exploit unexpected model behaviors to stress-test prosocial AI evaluations—and how open access to a model’s internals can help researchers understand why those te…
- arXiv cs.AIresearchMaking AI-Assisted Claims Independently Challengeable: Publication Authority and a Protocol for Falsifiable Publication Records
arXiv:2609.17631v2 Announce Type: replace Abstract: AI-assisted claims can appear authoritative when evidence, analysis, human authorization, presentation, and correction history describe different states. We develop Pub…
- arXiv cs.AIresearchOne Color Preprocessing Improves DSATUR
arXiv:2609.17633v1 Announce Type: new Abstract: The Graph Coloring Problem (GCP) is NP-hard and DSATUR stands as one of the fastest heuristics for it despite producing colorings that typically use more colors than state-…
- arXiv cs.AIresearchPhysics-Constrained Digital Twins for Sensor Integrity in Urban Pedestrian Flow: Detecting Stealthy False Data Injection with Conformal Guarantees
arXiv:2609.17635v1 Announce Type: new Abstract: City pedestrian counting systems now feed economic indicators, planning decisions and safety operations, yet the twins built on top of them treat the incoming stream as gro…
- arXiv cs.AIresearchWhat You Can't See Is Still What You Learn: A Preregistered Sixty-Society Confirmation That Evidence Masking Drives Compositional Generalization
arXiv:2609.17637v2 Announce Type: replace Abstract: Restricting what a module can read may improve what a system learns to compute. We test this in a preregistered confirmation with sixty four-cell systems sharing a froz…
- arXiv cs.AIresearchGVD: Governed Versioning and Deduplication for Document Repositories
arXiv:2609.17696v1 Announce Type: new Abstract: Document repositories evolve continuously. Guidelines and policies are revised, superseded, and re-uploaded, so the same content recurs in different wording and newer versi…
- arXiv cs.AIresearchNeMo Data Designer: An Extensible Framework for Multimodal Synthetic Data Generation
arXiv:2609.17699v1 Announce Type: new Abstract: We present NeMo Data Designer (NDD), an open-source, general-purpose framework for multi-modal synthetic data generation (SDG). Designed to be intuitive to use, NDD provide…
- arXiv cs.AIresearchA Systematic Evaluation of the COTQ Provincial Land Cover Product: Structural Consistency, Spectral Separability, and Relative Positioning Against ESA, ESRI, and Google Products
arXiv:2609.17731v1 Announce Type: new Abstract: High-resolution land use and land cover (LULC) products derived from Sentinel-2 imagery are widely used for environmental monitoring and land management, yet their performa…
- arXiv cs.AIresearchSAGE: Governed Artifact Generation from Enterprise Guidelines
arXiv:2609.17775v1 Announce Type: new Abstract: Enterprise guideline documents mix narrative text, complex tables, and embedded images, and converting them into structured work artifacts still takes two to three days of…
- arXiv cs.AIresearchA Four-Stage Decomposition of Word-Problem Solving and Mechanistic Fragility in LLM Math Reasoning
arXiv:2609.17804v1 Announce Type: new Abstract: Large language models solve grade-school math word problems with high accuracy, yet a single irrelevant clause inserted into the problem can collapse it. We reconcile these…
- arXiv cs.AIresearchLearning Heterogeneous Preferences
arXiv:2609.17847v1 Announce Type: new Abstract: Learning from human feedback has become a central paradigm for training modern AI systems, where models of human utility are used as reward models in policy learning. Exist…
- arXiv cs.AIresearchSNOMED CT Concept Recommendation from Masked Clinical Context
arXiv:2609.17855v1 Announce Type: new Abstract: Standardizing clinical language to SNOMED CT supports interoperability, analytics, and reusable phenotyping, but concept recommendation remains difficult when relevant conc…
- arXiv cs.AIresearchThe Inference Engineering Pareto Atlas: Which Optimizations Dominate the Cost, Quality, and Latency Frontier?
arXiv:2609.17863v1 Announce Type: new Abstract: LLM inference optimizations report speedups on different models, GPUs, prompts, and quality metrics, making them hard to compare or combine. We build a cost, quality, and l…
- arXiv cs.AIresearchDo Frontier Models Seek Safety Evidence Before Acting?
arXiv:2609.17865v1 Announce Type: new Abstract: Frontier models are often evaluated on how they respond to safety information once it is already in context. We study an earlier decision point: whether models choose to ac…
- arXiv cs.AIresearchOBC-Prune: Outcome-Based Calibration for Large Reasoning Model Pruning
arXiv:2609.17890v1 Announce Type: new Abstract: Large reasoning models (LRMs) generate long chain-of-thought traces before answering, creating significant inference overhead. Pruning can reduce this cost, but its effecti…
- arXiv cs.AIresearchMeasuring AI Leadership: Development and Validation of a Multidimensional Measure for AI-Native Organizations
arXiv:2609.17965v1 Announce Type: new Abstract: AI is changing what leaders must judge, explain, learn, and coordinate, yet existing measures do not capture these behaviors at the level needed to study leadership in AI-e…
- arXiv cs.AIresearchMemory Has Geometry: Non-Uniform Geometric Memory for Long-Horizon Personalized AI
arXiv:2609.17969v1 Announce Type: new Abstract: Long-term memory is becoming a core substrate for personalized AI, yet most systems still represent personalization as discrete records in a largely static latent space, ac…
- arXiv cs.AIresearchMultimodal Conditioning of Fine-Tuned Stable Diffusion XL for Controllable and Culturally Faithful Ulos Motif Generation
arXiv:2609.17987v1 Announce Type: new Abstract: The traditional Batak Ulos weaving industry faces growing challenges in producing diverse, innovative motifs due to limitations in conventional, manually driven design meth…
- arXiv cs.AIresearchMissing Bridges: Composition-Aware Active Imitation Learning
arXiv:2609.18004v1 Announce Type: new Abstract: Active imitation learning reduces expert effort by allowing a learner to request the demonstrations it needs. Existing methods typically select these requests for their exp…
- arXiv cs.AIresearchAnchoring What Matters: A Dual-Level Learning Framework for Visually-Grounded Multimodal Reasoning
arXiv:2609.18057v1 Announce Type: new Abstract: Reinforcement learning with verifiable rewards (RLVR) has significantly improved the reasoning capabilities of large vision-language models (LVLMs). However, standard on-po…
- arXiv cs.AIresearchThe Other Half of the Memory Wall: Serving 35B MoEs from SSD with Trained Routing Prediction
arXiv:2609.18063v2 Announce Type: replace Abstract: Mixture-of-experts (MoE) inference on consumer hardware is bounded by weight memory: a 35B-class model is 19.5GB at 4-bit, and sparsity shrinks the compute per token, n…
- arXiv cs.AIresearchTeaching AI, Robotics, & Community: A Hubs-Based K-12 Education Framework for Reaching Rural Schools
arXiv:2609.18072v1 Announce Type: new Abstract: K-12 robotics and AI education remains difficult to scale, especially in rural regions lacking sustained technical mentorship. Programs like FIRST provide competition pathw…
- arXiv cs.AIresearchDecodability is Not Causality: Dissociating Probe Readouts from Behavioral Drivers via SAE Decomposition
arXiv:2609.18080v1 Announce Type: new Abstract: Linear probes can decode safety-relevant concepts such as truthfulness from language-model activations, but probe accuracy may show only decodability, not that the features…
- arXiv cs.AIresearchWhen Is Graph Structure Worth Its Cost? The Case for Structure Pricing in Retrieval-Augmented Generation
arXiv:2609.18099v1 Announce Type: new Abstract: Graph-based retrieval-augmented generation (RAG) can help answer questions that require information from many documents. However, building a graph often requires many langu…
- arXiv cs.AIresearchTime-Aligned Evolving Concept Graphs for Scientific Relation Forecasting
arXiv:2609.18163v1 Announce Type: new Abstract: Forecasting scientific relations can guide discovery by identifying promising connections before they emerge. Existing approaches often model concept semantics and graph st…
- arXiv cs.AIresearchRe2A: Situated Conversational Recommendation via Rubric-based Preference Reasoning and Alignment
arXiv:2609.18249v1 Announce Type: new Abstract: Real-world recommendation scenarios are commonly grounded in shared physical environments during user-recommender interactions. This motivates situated conversational recom…
- arXiv cs.AIresearchREPAIR: Resolving Long-Tail Confusion in Scientific Retrievers via Fact-Verified Iterative Refinement
arXiv:2609.18262v1 Announce Type: new Abstract: Precise retrieval of scientific information is fundamentally constrained by long-tailed concepts and high fact-sensitivity of scientific corpora. These challenges often lim…
- arXiv cs.AIresearchBENCHCOMPASS: From Scores to Signals for Training and Harness Decisions in Payment-Domain LLMs
arXiv:2609.18270v1 Announce Type: new Abstract: Payment operations are a critical financial infrastructure, but the value of large language models in this domain remains unclear because payment rules change quickly, evid…
- arXiv cs.AIresearchBuilding Trust in Artificial Intelligence: A Necessity for Railway Applications
arXiv:2609.18278v2 Announce Type: replace Abstract: Artificial Intelligence (AI) is currently only applied to non-safety critical applications due to the strict standards and regulations for railway industries. We propos…