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2026.06.02arXiv cs.AI
Position Paper: Post-Solve Robustness in Decision Engines: Feasible Regions and Smoothness Under PerturbationsMixed-Integer Linear Programming (MILP) decision engines routinely output nominally optimal plans for high-stakes industrial systems. Yet deployment rarely matches solve-time assumptions: small perturbations in costs, demands, or resource availability can invalidate feasibility or trigger discontinuous shifts to quali…
↗2026.06.02arXiv cs.AIEmergent Collaborative Deliberation in Multi-Model AI Systems: A BFT-Derived Protocol for Epistemic SynthesisWe present the Consilium Protocol, a Byzantine Fault Tolerance-derived architecture for structured multi-model AI deliberation that treats inter-model disagreement as epistemic signal rather than error. The protocol assigns engineered cognitive personas to language models -- separating what a model is from how it reas…
↗2026.06.02arXiv cs.AIDeliberative Curation: A Protocol for Multi-Agent Knowledge BasesAs AI agents transition from isolated tools to collaborative participants in shared knowledge ecosystems, governing collective knowledge curation becomes a critical challenge. Human platform governance mechanisms do not transfer directly: agent statelessness undermines deterrence-based sanctions, model homogeneity vio…
↗2026.06.02arXiv cs.AIAgents on a Tree: Pathwise Coordination for Multi-Objective Molecular OptimizationMulti-objective molecular optimization requires searching vast chemical spaces under conflicting objectives, where early design decisions strongly constrain downstream outcomes. Existing methods typically rely on a single policy or fixed scalarization, which limits their ability to represent diverse trade-offs and to…
↗2026.06.02arXiv cs.AIOptimal Transport-based Permutation-Invariant Bayesian Optimization of Offshore Wind Farm LayoutsBayesian Optimization (BO) is widely and successfully adopted for solving optimization problems having an expensive-to-evaluate, black-box, and non-convex objective function. However, the vanilla BO algorithm is not able to exploit possible symmetries characterizing the target problem. An intuitive case is given by op…
↗2026.06.02arXiv cs.AIMindGames Arena Generalization Track: In2AI Solution with Delayed Per-Step Reward AttributionTraining language model agents for multi-agent strategic interaction presents a core difficulty: the quality of any action may depend on future events that never materialize, on moves that violate game rules, or on decisions made by other players. Standard reinforcement learning assumes that rewards can be assigned at…
↗2026.06.02arXiv cs.AIUniversal Quantum TransformerClassical continuous-space neural networks fundamentally struggle to lock into exact mathematical symmetries, such as modular arithmetic and non-commutative algebra. To approximate these discrete logical rules, they often rely on massive parameter scaling, resulting in stochastic instability even after delayed general…
↗2026.06.02arXiv cs.AIGrokers: Bottom-Up Inductive Comprehension and Write-Time Intelligence over Typed Knowledge GraphsWe present Grokers, an architecture for building persistent, structured comprehension of typed knowledge graphs through bottom-up inductive traversal of dependency subgraphs. Unlike retrieval-augmented generation (RAG), which pays full comprehension cost at every query, Grokers pushes intelligence to write time: auton…
↗2026.06.02OpenAICodex is becoming a productivity tool for everyoneThe Next Era of Knowledge Work report explores how Codex is transforming productivity through AI-powered research, data analysis, workflow automation, and content creation.
↗2026.06.01OpenAIOur views on AI policy and political advocacyOur approach to AI policy and political advocacy, transparency, support for thoughtful regulation and AI safety, and that no outside political group speaks on the company’s behalf.
↗2026.06.01Hacker News (AI)AI Agent Guidelines for CS336 at Stanford
↗2026.06.01Hacker News (AI)DuckDuckGo makes its 'no-AI' search engine easier to access as its traffic booms
↗2026.06.01Hacker News (AI)Florida sues OpenAI and Sam Altman over AI risks
↗2026.06.01Hugging FaceIntroducing Mellum2: A 12B Mixture-of-Experts Model by JetBrains
↗2026.06.01Hugging FaceBeyond LLMs: Why Scalable Enterprise AI Adoption Depends on Agent Logic
↗2026.06.01Hacker News (AI)When AI Crosses the Line: The Matplotlib Incident
↗2026.06.01OpenAIBuilding the infrastructure for the Intelligence Age in MichiganOpenAI breaks ground on a 1GW data center project in Michigan as part of Stargate, building AI infrastructure to expand access, create jobs, and support communities.
↗2026.06.01OpenAIOpenAI frontier models and Codex are now available on AWSOpenAI frontier models and Codex are now generally available on AWS, giving enterprises a new path to build with OpenAI through the AWS environments, controls, and procurement workflows they already use. Customers can get started with OpenAI on AWS and move faster from evaluation to production.
↗2026.06.01Hugging FaceWelcome NVIDIA Cosmos 3: The First Open Omni-model for Physical AI Reasoning and Action
↗2026.06.01arXiv cs.AIPhyDrawGen: Physically Grounded Diagram Generation from Natural LanguageGenerating physics diagrams from text requires strict adherence to physical laws. While current generative models produce visually plausible outputs, they systematically hallucinate force vectors, ignore conservation laws, and violate geometric constraints. We present PhyDrawGen, a neuro-symbolic pipeline that decoupl…
↗2026.06.01arXiv cs.AIPhysically Viable World Models: A Case for Query-Conditioned Embodied AIWorld models for embodied AI must be physically viable: constructed to answer intervention queries by representing the physical structure governing action outcomes, rather than merely predicting future observations. Existing observation-predictive world models can produce visually plausible but physically wrong rollou…
↗2026.06.01arXiv cs.AITransforming and Encoding FTS for SAT Solving: What Helps, What Hurts (Extended Version)Factored tasks are a classical planning representation that extends SAS+ with limited forms of disjunctive preconditions, conditional effects, and angelic nondeterminism. This allows for a more compact representation of tasks than traditional formalisms such as STRIPS or SAS+, and supports a wide range of task transfo…
↗2026.06.01arXiv cs.AIProcedural Generation of First Person Shooter Maps using Map-ElitesWe investigate the application of MAP-Elites (a well-known quality diversity algorithm) to design levels for First-Person Shooter (FPS) games. We consider two well-known map representations (All-Black and Grid-Graph) and introduce two novel representations (Point-Line and Spatial-Layout) that improve the characterizat…
↗2026.06.01arXiv cs.AIUncertainty-Aware and Temporally Regulated Expert Advice in Reinforcement Learning for Autonomous DrivingExploration in reinforcement learning for autonomous driving is inherently unsafe: agents must experience novel behaviors to learn, yet exploration can lead to collisions or off-road driving. We propose an uncertainty-aware framework that leverages expert advice to guide exploration while avoiding long-term dependence…
↗2026.06.01arXiv cs.AIHarness Updating Is Not Harness Benefit: Disentangling Evolution Capabilities in Self-Evolving LLM AgentsLLM agents are increasingly deployed as systems built around editable external harnesses, including prompts, skills, memories and tools, that shape task execution without changing model parameters. Harness self-evolution adapts such agents by updating these harnesses from execution evidence. Yet it remains unclear whe…
↗2026.06.01arXiv cs.AIEHRBench: An Automated and Reliable EHR-based Benchmark for Clinical Decision Making with LLMsClinical decision-making (CDM) is central to real-world clinical workflows, where clinicians infer diagnoses, select treatments, or anticipate future health outcomes under incomplete evidence. LLMs are increasingly used to support these decisions due to strong language capabilities, broad biomedical knowledge, and eff…
↗2026.06.01arXiv cs.AIStructure-Induced Information for Rerooting Levin Tree SearchSubgoal-based policy tree search, which uses a policy to guide search, is effective for complex single-agent deterministic problems but often relies on explicit subgoal generation that can incur substantial overhead and hinders scalability. In this paper, we overcome these limitations by using a learned ``rerooter'' t…
↗2026.06.01AnthropicAnthropic confidentially submits draft S-1 to the SECAnthropic confidentially submits draft S-1 to the SEC
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↗2026.05.29OpenAIBoston Children’s uses AI to unlock new diagnosesBoston Children’s Hospital uses OpenAI technology to improve patient care, reduce operational burden, and help diagnose more than 40 rare disease cases.
↗2026.05.29OpenAIHow Braintrust turns customer requests into code with CodexHow Braintrust engineers use Codex with GPT-5.5 to run experiments and code faster.
↗2026.05.29Hacker News (AI)Is AI causing a repeat of frontend’s lost decade?
↗2026.05.29Hacker News (AI)Real-time LLM Inference on Standard GPUs: 3k tokens/s per request
↗2026.05.29Kimi1.46.0What's Changed docs: announce evolution to Kimi Code successor project by @RealKai42 in #2377 docs: fix router auto language redirect by @RealKai42 in #2378 feat(shell): update welcome tip link to kimi.com/code and support styled Text by @jackfish212 in #2390 fix(acp): replay session history on load by @bugkeep in #21…
↗2026.05.29arXiv cs.AIBehavior-Induced Mirror-Prox Temporal-Difference Learning for Faster Off-Policy PredictionGradient temporal-difference methods provide stable off-policy prediction with linear function approximation, but their practical performance is strongly affected by the geometry induced by the auxiliary-variable metric. Existing Mirror-Prox TD methods typically use the feature covariance metric, whereas hybrid TD met…
↗2026.05.29arXiv cs.AIBehavior-Aware Auxiliary Corrections for Off-Policy Temporal-Difference PredictionTemporal-difference learning with function approximation can be unstable under off-policy sampling. TDC stabilizes off-policy TD through an auxiliary covariance correction, and TDRC further regularizes this correction in a single-timescale recursion. This paper studies a behavior-aware replacement of the auxiliary cov…
↗2026.05.29arXiv cs.AIThe Cognitive Categorical Transformer: Category-Theoretic Inductive Biases for Language ModelingThe Cognitive Categorical Transformer (CCT) is a 306M-parameter architecture that augments a pretrained GPT-2 Small backbone with cognitively grounded components derived from category theory and several inspirations from cognitive science. Under a matched-step protocol (215,000 optimizer steps, matched data, matched o…
↗2026.05.29arXiv cs.AIUltra-Reduced-Impact-Encased-Logging (URIEL): propose a new method for selective sustainable logging and post-harvest silvicultural treatment in tropical forest using airborne robotics systemsTropical forests worldwide are under intense deforestation pressure driven by economic and political interests, and scientific evidence suggests this deforestation contributes to climate change. This paper proposes a novel logging method for tropical forests, Ultra-Reduced-Impact-Encased-Logging (URIEL). This new meth…
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