Hoeffding Concept Bottleneck Models (HCBM) leverage the Hoeffding functional decomposition of gradient-boosted trees for non-linear and sparse aggregation of concept scores, improving explainability, and outperform linear CBM in classification and object detection tasks.

DAStatFormer is a hybrid multibranch Transformer that uses statistical features from multiple domains to classify DAS events efficiently, achieving 99.4% accuracy with fewer parameters and lower inference cost.

BitsMoE is an efficient quantization framework for Mixture-of-Experts (MoE) large language models. It uses SVD to decompose each MoE layer into a shared basis and expert-specific spectral factors, preserving the shared basis without quantization to maintain cross-expert structure. An integer linear programming formulation minimizes reconstruction loss under a fixed bit budget. Experiments show that BitsMoE significantly reduces accuracy degradation in ultra-low-bit regimes, achieving 12.3× quantization speedup, 27.83 percentage point average accuracy improvement, and 1.76× decoding speedup over GPTQ on Qwen3-30B-A3B-Base at 2 bits.

This paper traces the evolution of probability theory from games of chance to Bayesian inference, revealing it as a transformation of rationality itself. It argues that while probability quantifies uncertainty for well-defined propositions, it fails to capture the vagueness of concepts. Fuzzy logic and deep learning are examined as complementary frameworks, and the article concludes that contemporary scientific rationality must explicitly articulate uncertainty, vagueness, and inference.

Global anomaly detection models in multi-product manufacturing suffer from blind spots due to expanded decision boundaries. The proposed product-aware autoencoder restricts learning to grade-specific distributions, achieving 100% detection accuracy in stress tests. This work advocates for mode-aware diagnostic architectures.

Grokers is an architecture that builds persistent, structured comprehension of typed knowledge graphs via bottom-up inductive traversal of dependency subgraphs, shifting intelligence to write time to avoid LM costs at query time. It proves three theorems and offers a deterministic alternative to embedding-based semantic search.

Introducing the Universal Quantum Transformer (UQT), a novel quantum-native architecture that leverages multi-qubit physics for exact mathematical reasoning, achieving perfect learning of modular arithmetic and non-commutative algebra on just 5 qubits, with deterministic generalization termed 'crystallization'.

This paper introduces a method with delayed per-step reward attribution, eligibility gating, asynchronous rollout generation via vLLM, curriculum-based opponent sampling, and multi-level stratified batch construction. An 8B parameter open-source model trained with this approach matched or surpassed larger proprietary systems like GPT-5 in the NeurIPS 2025 MindGames Arena benchmark, winning first place in both the Open and Efficient tracks.

Proposes a Permutation-Invariant Bayesian Optimization (PIBO) approach based on Optimal Transport for optimizing offshore wind farm layouts. Compared to vanilla BO, PIBO exploits symmetries, yielding better layouts with roughly half the computation time.

Multi-objective molecular optimization requires searching vast chemical spaces under conflicting objectives. Existing methods rely on single policy or fixed scalarization, limiting trade-off representation. We propose ATOM, a multi-agent framework that formulates molecular optimization as tree-structured search. Agents coordinate along different paths, maintaining alternative evolution trajectories. Global memory supports balanced exploration. Experiments show improved Pareto coverage and hypervolume over strong baselines.

A deliberative curation protocol combining three governance layers (knowledge artifact lifecycle, reputation-weighted deliberative voting, and graduated sanctions) is proposed. Agent-based simulation with 100 agents shows improved resilience under adversity compared to majority voting, with commit-reveal vote concealment being the most impactful component.

We present the Consilium Protocol, a Byzantine Fault Tolerance-derived architecture for structured multi-model AI deliberation that treats inter-model disagreement as epistemic signal. Assigning cognitive personas to models, we show that persona, not model, determines epistemic behavior; RLHF creates domain-specific blind spots; and the protocol is unbiased. Cost: $217.

This position paper argues that Mixed-Integer Linear Programming (MILP) decision engines suffer from a post-solve robustness gap: small perturbations in costs or demands can invalidate feasibility or cause discontinuous solution shifts. The authors propose a new layer that audits the solved incumbent, formalizing an ε-near-optimal feasible neighborhood in parameter space and solution smoothness in decision space. They synthesize existing work from sensitivity analysis, robust optimization, neighborhood search, adversarial testing, and learning-based methods, and call for certified inner approximations, probabilistic robustness estimation, adversarial margins, and learning-based prediction aligned with solver-backed verification. A compact reporting template and evaluation protocol are provided to make robustness a first-class output.

The act proposes the creation of a U.S. sovereign wealth fund focused on artificial intelligence to boost innovation and national competitiveness.

NVIDIA launched Cosmos 3 (unified multimodal world model), Nemotron 3 Ultra (efficient 550B LLM), and RTX Spark (personal AI superchip). Also covered: MiniMax M3, Qwen3.7-Plus, JetBrains Mellum2, agent ecosystems, and infrastructure updates.

This post demonstrates how to implement Open Authorization (OAuth) Code flow as an inbound authorization mechanism for MCP servers hosted on Amazon Bedrock AgentCore Gateway. By the end of this guide, you will have a production-ready setup where each AI assistant request is authenticated with a valid user identity token issued from your organization’s identity provider.

The full system prompt for Meta's AI support system has been leaked, revealing internal instructions including language rules, issue handling, and domain agent ranking.

Catch and fix usability issues automatically as you ship.

Jan is an open-source, local AI assistant that runs on your device, offering privacy and customization with various models.

Branda is an AI-powered brand identity generator that creates a complete brand kit (strategy, logo, palette, type, etc.) from just a name and idea. It offers guided flows, visual prompts, and exports usable assets.

Nine new security vulnerabilities discovered in X.Org Server and XWayland, mostly via AI. Vulnerabilities range from buffer overflows to use-after-free. Patches released in xorg-server 21.1.23 and xwayland 24.1.12.

NVIDIA announced JetPack 7.2 and NemoClaw support on Jetson, bringing agentic AI to edge devices. The updates include Yocto support, CUDA 13, performance boost, MIG support, and NemoClaw framework for deploying AI agents in robotics, inspection, and industrial automation.

The Next Era of Knowledge Work report explores how Codex is transforming productivity through AI-powered research, data analysis, workflow automation, and content creation.

Developers are furious over Microsoft's new usage-based billing for GitHub Copilot, reporting that monthly credits are consumed in hours, leading many to consider switching to alternatives like OpenRouter.

We build NVIDIA Apex from source, detect fused kernels, and benchmark FusedAdam, FusedLayerNorm, and torch.amp in Transformer training.

GitHub Copilot has adopted a usage-based pricing system using credits. Costs vary by model and tokens, with advanced models being more expensive. Users report high credit consumption even for simple tasks, and caution is needed with Auto mode.

How one Normal engineer used AI agents to build a practical verification stack on top of CIRCT: simulation, formal verification, mutation testing, and more.

aweskill is a CLI-first Skill package manager designed for AI coding agents to operate autonomously. It allows agents to install, update, bundle, and manage Skills via natural language after a one-time bootstrap. Includes built-in meta-skills for routine management and repair.

When AI Gateway credits are depleted (zero balance), all requests are blocked - including those that should use BYOK (Bring Your Own Key) credentials. This happens regardless of whether BYOK is configured via dashboard integrations or programmatic providerOptions.byok.

Together AI optimizes MiniMax M3 serving with KV-block-major sparse attention, paged MSA decode, optimized index scoring, and a Rust-based multimodal gateway, achieving 81–125% throughput improvements across concurrency levels.