AI news archive.
19,861 articles, newest first, from the outlets listed on the sources page.
- Engadget AIagentsGoogle brings Gemini Personal Intelligence to Android Auto
In the coming months, the feature will also roll out to cars with Google built-in.
- Ai2 BlogsafetyFairStress: A deeper evaluation of fairness in LLM decision-making
FairStress is a new benchmark that reveals demographic differences in how LLMs defend and explain their decisions, even when their final choices appear fair.
- LessWrongsafety1000 Years of AI Safety
A three-year AI pause could buy 1000 years' worth of AI safety work. See: https://1000yearsofaisafety.com How much AI safety work a pause produces, in years of the whole 2025 AI safety field's work . The government bans…
- OpenAI NewsagentsTerminal X matches senior investor judgment 88.6% with GPT-6.1
Terminal X’s Eval Agent grades outputs against a 54-criterion rubric, catching 25% more deviances from a fund’s mandate with GPT-6.1 Sol.
- TechRadar AIcommunity'We love a good challenge': Logitech head tells us why the AI age could revolutionize collaboration as we know it, as it reveals its biggest product overhaul in years
Mainstream AI news from a large tech publication.
- Tom's Guide AImodelsFirst NotebookLM, now Gems — Google's AI tool name changes are getting ridiculous
Consumer AI launches, tools, and practical coverage.
- Guardian AIcommunityHollywood AI-listers: is the technology ready to rival flesh-and-blood film stars?
As a freaky Val Kilmer doppelganger stars in a new western and faux starlet Tilly Norwood is set for her feature debut, experts are split on whether mainstream adoption is a long way down the line – or just around the co…
- Guardian TechnologycommunityGooglebook review: Google’s new laptops are woefully underbaked
Great hardware let down by software flaws on these pricey machines that combine ChromeOS with Android Google’s attempt to create a new type of laptop to compete with Windows and macOS machines is finally here, combining…
- Latent Spacemodels[AINews] not much happened today
Congrats to DeepSeek V4.1 Flash 1017, MiniMax M3.1 Flash, and Mercury 3 (details below) but they’re not going to be in super wide use just yet.
- Latent Spacemodels[AINews] not much happened today
Congrats to DeepSeek V4.1 Flash 1017, MiniMax M3.1 Flash, and Mercury 3 (details below) but they’re not going to be in super wide use just yet.
- Guardian AIcommunityDon’t be fooled. The AI that was supposed to save us time is doing just the opposite | Gaby Hinsliff
The government says it can transform the state with AI, but it is no match for the resulting stream of machine-generated slop. And we all pay the cost Another morning, another avalanche of emails. Even after a guilty cul…
- NVIDIA BlogstartupsSpain-Based Startups Advance Regional Innovation With Barcelona Supercomputing Center
The Barcelona Supercomputing Center (BSC)’s AI Factory Accelerator Programme, now in full operation following a pilot initiative, gives startups access to sovereign compute, technical support and training to support inno…
- Guardian Technologysafety‘These risks are real’: the threat of AI bioweapons – podcast
In his annual speech on threats to the nation, Sir Ken McCallum, the head of the UK’s intelligence service, MI5 , warned that AI had the potential to ‘change the stakes’ on existing and even new bioweapons. To find out w…
- arXiv cs.AIagentsStructured Authority Injection: Persistent Human Control for LLM Agents via Typed MCP Overrides
arXiv:2610.22373v1 Announce Type: new Abstract: LLM-based agents are increasingly used as autonomous orchestrators in distributed and multi-agent systems, yet a control gap remains: no protocol-level mechanism allows hum…
- arXiv cs.AIresearchRethinking User Encoders: Routing Diffusion States for Scenario-Adaptive User Representation
arXiv:2610.22400v1 Announce Type: new Abstract: Existing large language model (LLM)-based user encoders serialize heterogeneous behavioral logs and compress them into static representations through autoregressive (AR) pr…
- arXiv cs.AIresearchFrom Events to Reasoning: Hierarchical Rule Composition over Explicit States
arXiv:2610.22403v1 Announce Type: new Abstract: What a reasoning system emits is a conclusion; what it owes is a justification. Producing one requires every operation to be admissible on the facts actually available, the…
- arXiv cs.AIagentsECHOES: Seeing Beyond the Current Image via Recursive History Compression and Privileged On-Policy Distillation
arXiv:2610.22408v1 Announce Type: new Abstract: Long-horizon GUI agents rely on visual history to maintain task states, but retaining historical screenshots increases visual-token usage and inference costs, while textual…
- arXiv cs.AIagentsSensitivity Analysis of Decision Rules in an Agent-Based Agro-Ecological Model
arXiv:2610.22420v1 Announce Type: new Abstract: Agent-based models are well-suited for modelling agro-ecological systems for decision-making, yet turning their simulations into actionable insight requires identifying whi…
- arXiv cs.AIagentsPRIME: Towards Verifiable Evidence-Grounded Reasoning in LLM Agents
arXiv:2610.22426v1 Announce Type: new Abstract: LLM agents are used to check records against an organization's requirements, for example whether a vulnerability report is ready for investigation. Requirements often allow…
- arXiv cs.AIresearchFrom Natural Language Intent to Executable Control: Hierarchical Feedback-Guided LLM Planning for Multi-component Cyber-Physical Systems
arXiv:2610.22441v1 Announce Type: new Abstract: Large language models (LLMs) provide a convenient interface for translating natural language commands into task plans for cyber-physical systems (CPSs). However, two gaps h…
- arXiv cs.AIresearchNull Controls Are Necessary but Not Sufficient: Evaluating Acceptance Guards for Scientific Discovery and Interpretability
arXiv:2610.22445v1 Announce Type: new Abstract: Automated discovery systems propose scientific explanations and test which to accept. Does passing a test establish the intended claim? We develop four executable operation…
- arXiv cs.AIresearchLearnable Splines for Unstructured Neural Operators
arXiv:2610.22446v1 Announce Type: new Abstract: Neural operators approximate solution operators of partial differential equations at a fraction of the cost of numerical solvers. Efficient grid-based architectures such as…
- arXiv cs.AIresearchFunctional Welfare for AI Safety
arXiv:2610.22460v1 Announce Type: new Abstract: AI welfare is generally treated purely as an ethical issue rather than also as a safety issue. We argue this is a mistake. Whatever their moral status, models exhibit welfa…
- arXiv cs.AIagentsAuthor-in-the-loop Agentic Reproducibility Auditing for a Machine Learning Conference
arXiv:2610.22465v1 Announce Type: new Abstract: Reproducibility checks during peer review require a shared understanding of what authors' code is expected to reproduce. We present an author-in-the-loop collaborative audi…
- arXiv cs.AIagentsHarness-Delta Attribution: Dissecting Gains From Harness Evolution
arXiv:2610.22466v1 Announce Type: new Abstract: Harness evolution automatically optimizes the prompts, skills, tools, and orchestration code around a fixed-weight model, offering a way to improve agentic systems without…
- arXiv cs.AIagentsTesting the Planning Claims of LLM-Based Agents against Formal Semantics
arXiv:2610.22469v1 Announce Type: new Abstract: LLM-based agents are increasingly credited with the competences of practical reasoning: planning, monitoring, and correcting their own actions. Their success is attributed…
- arXiv cs.AIresearchAre Large Reasoning Models Good Everyday Reasoners? A Comparison with Non-Reasoning Models on Logical Reasoning Tasks
arXiv:2610.22538v1 Announce Type: new Abstract: Large reasoning models (LRMs) that leverage test-time computation achieve strong performance on mathematical and scientific benchmarks and are increasingly deployed in real…
- arXiv cs.AIagentsFRACTAL: A Self-Similar Multi-Agent Orchestration Architecture with Formal Communication, Convergence, and Depth Bounds
arXiv:2610.22561v1 Announce Type: new Abstract: We present FRACTAL, a self-similar multi-agent architecture for recursive goal decomposition, in which the same five-component organizational pattern -- Orchestrator, Ensem…
- arXiv cs.AIresearchRepairing LLM-Generated Specifications with Deterministic Diagnosis
arXiv:2610.22568v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as formalizers: given a reasoning problem expressed in natural language, they produce a formal specification that a symbo…
- arXiv cs.AIagentsAt the Limits of Computability: Steps Towards Autonomous AI Discovery on the Busy Beaver Frontier
arXiv:2610.22603v2 Announce Type: replace Abstract: Recent breakthroughs in AI for mathematics---ranging from Olympiad medal performances to resolving long-standing open conjectures---have rapidly expanded what automated…
- arXiv cs.AIagentsFrom Relevant Memories to Sufficient Evidence: Rethinking Memory Utilization in LLM Agents
arXiv:2610.22668v1 Announce Type: new Abstract: Long-term memory enables LLM agents to reuse past experiences, yet retrieving relevant memories does not necessarily provide sufficient evidence for answering a query. Esse…
- arXiv cs.AIagentsNot All Graphs Are Maps: A Task-Agnostic Exploration Framework for Mobile GUI Navigation
arXiv:2610.22672v1 Announce Type: new Abstract: Modern mobile GUI agents can perceive visible screens and execute local actions, but they still lack persistent app-specific navigation knowledge: where functions live, whi…
- arXiv cs.AIresearchFlexUMM: Flexible Representation Learning for Unified Multimodal Models
arXiv:2610.22682v1 Announce Type: new Abstract: Unified multimodal models (UMMs) can integrate understanding and generation within a single backbone. However, it is commonly known that these two capabilities can cause co…
- arXiv cs.AIresearchRepair, Retry, and the Cost of Hindsight: Verifier Feedback in Formal Theorem Proving
arXiv:2610.22698v1 Announce Type: new Abstract: Verifier-guided self-repair conditions a model on feedback from failed attempts before it tries again, without weight updates. Yet two findings in prior work are in tension…
- arXiv cs.AIresearchBrain-Aligned Multimodal LLMs for Social and Emotional Understanding of Cartoon Movies
arXiv:2610.22706v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) offer scalable annotations of social and affective content, but their temporal agreement with human judgments and neural predictive…
- arXiv cs.AIresearchGlobeBench: Evaluating Text-Based World Model Capabilities for Scalable Environment Simulations
arXiv:2610.22708v1 Announce Type: new Abstract: Text-based world models have recently shown potential to simulate complex RL environment state transitions for a diverse set of use cases. However, no standardized benchmar…
- arXiv cs.AIresearchLEMON: Equivariant Learning over Attention Maps for Zero-Shot Misbehavior Monitoring on New LLMs
arXiv:2610.22723v1 Announce Type: new Abstract: Large language models exhibit misbehaviors that hinder deployment in high-stakes settings. One approach to monitor such failures is to use an external LLM as a monitor, but…
- arXiv cs.AIresearchGraph Serializations for Reasoning LLMs: A Study Across Knowledge Extraction and Structural Reasoning
arXiv:2610.22734v1 Announce Type: new Abstract: The way a knowledge graph is serialized as text for inclusion into LLM context can substantially affect downstream LLM performance, with prior work reporting tens of percen…
- arXiv cs.AIagentsR$^2$Orch: Recursive Self-Improvement for Agent Orchestration via Self-Play within a Skill-Internalization Loop
arXiv:2610.22740v2 Announce Type: replace Abstract: In recent years, agentic orchestration has been widely applied to solve complex human tasks. However, existing orchestration learning still faces key challenges, includ…
- arXiv cs.AIresearchBetween Spoilers and Guesswork: Avoiding Over-Specification in Coding Benchmarks
arXiv:2610.22760v1 Announce Type: new Abstract: Benchmarks drive AI progress, but are hampered by task under-specification and over-specification. Task under-specification causes guesswork, where solutions have to make t…
- arXiv cs.AIresearchStoBasket: Joint Upsell and Cross-Sell Optimization for Contribution Margin
arXiv:2610.22768v1 Announce Type: new Abstract: Retail recommenders rank relevance, but retailers earn contribution margin: an upsell earns the margin difference over the item it replaces, whereas a cross-sell earns its…
- arXiv cs.AIagentsWhen Can You Trust an Agent's Own Verifier? Stress-Testing Counterfactual Rationale Verification Under Search Pressure and Oracle Access
arXiv:2610.22779v1 Announce Type: new Abstract: Automated agent design increasingly trusts a single score to decide whether a change is an improvement -- but a score optimized aggressively enough ceases to measure what i…
- arXiv cs.AIresearchCompression Precedes, Content Decides: Emergent Misalignment in Reward Models
arXiv:2610.22805v1 Announce Type: new Abstract: Emergent Misalignment - the out of domain generalization of narrow harmful fine-tuning first shown by Betley et al. [2025] has been widely studied in language models but no…
- arXiv cs.AIresearchWorld Action Critic (WAC) Model: Joint Foresight and Criticism for Policy Learning
arXiv:2610.22825v1 Announce Type: new Abstract: World models have shown considerable promise in sequential decision-making by anticipating the consequences of actions and providing predictive foresight for policy learnin…
- arXiv cs.AIresearchEvo-B&B: Behavior-Aware LLM-Guided Joint Evolution of Branching and Node Selection Policies for MILP
arXiv:2610.22861v1 Announce Type: new Abstract: In branch-and-bound for Mixed-Integer Linear Programming (MILP), branching and node selection are two critical and tightly coupled decisions, yet most existing learning-bas…
- arXiv cs.AIagentsMS-Eval: Benchmarking Sub-Agent Delegation and Orchestration in MCP-Intensive Working Scenarios
arXiv:2610.22869v1 Announce Type: new Abstract: LLM agents are increasingly integrated into real-world works, yet they must handle diverse domain-specific tools and complex multi-sub-task problems that sequential tool in…
- arXiv cs.AIresearchShadowFPT: Backdooring Federated Prompt Tuning via Shadow Triggers
arXiv:2610.22871v1 Announce Type: new Abstract: Federated Prompt Tuning (FPT) adapts large vision--language models by freezing the pretrained backbone and optimizing only lightweight prompt parameters across clients. Alt…
- arXiv cs.AIresearchLook Back, Correct Forward: Error Feedback Calibration for Time Series Forecasting
arXiv:2610.22872v1 Announce Type: new Abstract: Time series forecasting models are increasingly deployed in continuously evolving environments. After a forecast is issued, future observations gradually arrive and reveal…
- arXiv cs.AIresearchToPA: Block-wise Toeplitz Adaptation for Expressive and Efficient Fine-Tuning
arXiv:2610.22883v2 Announce Type: replace Abstract: Parameter-Efficient Fine-Tuning (PEFT) has emerged as a prevalent strategy for adapting large pre-trained models. Among PEFT techniques, reparameterization-based method…
- arXiv cs.AIagentsWhen to Forget: Risk-Controlled Context Adaptation for Long-Horizon Agents
arXiv:2610.22897v1 Announce Type: new Abstract: Long-horizon agents learn from failure, but the value of a failure record can change as execution progresses. We study when retaining, compressing, or removing the same his…