MiniMax releases M3, an open-weight model featuring a one-million-token context window, top-tier coding performance, and native multimodality. First open-source model combining these three capabilities.
Nvidia launches three physical AI models at GTC Taipei: Cosmos 3 (world model), Alpamayo 2 Super (scaled-up autonomous driving model), and an open reference platform for humanoid robots.
OpenAI breaks ground on a 1GW data center in Michigan as part of Stargate project. The infrastructure aims to expand AI access, create jobs, and support local communities.
OpenAI frontier models and Codex are now generally available on AWS. Enterprises can access OpenAI through existing AWS environments, controls, and procurement workflows, accelerating the path from evaluation to production.
SoftBank commits €45 billion in France for AI data center development in an initial phase, with €75 billion potential subject to expansion. The project targets up to 5 GW capacity.
Dell delivered the first Vera Rubin NVL72 server to CoreWeave, integrating 72 GPUs in a single rack. This infrastructure marks a key milestone in compute density for AI.
Qwen 3.7 Plus from Alibaba is now available on Vercel AI Gateway. This multimodal model unifies vision and language for AI agents, covering GUI/CLI, coding, and visual tasks. Access via SDK with transparent pricing and zero platform fees.
NVIDIA releases Cosmos 3, an open omni-model for physical AI that reasons and acts. The model processes video, text, and images to understand real-world physics and generate robotic actions.
DecomposeR, a deep research framework, trains Qwen3-8B in two RL stages: planner RL learns typed DAG structures and query decomposition, then answerer RL learns branch execution and synthesis. Achieves 5.1-8.0 point improvements on long-form benchmarks through explicit planning and structured rewards.
LinTree improves LLM reasoning by explicitly representing the tree structure of search traces. Researchers show raw access to search history alone fails to reliably outperform LLM-guided heuristic search. Adding parent pointers to explicitly represent the linearized tree structure improves performance and search efficiency on Blocks World, grid Navigation, and Sokoban.
Study on harness self-evolution (prompts, skills, memories, tools) in LLM agents. Analyzes two capabilities: harness-updating (producing useful updates) and harness-benefit (benefiting from them). Findings: harness-updating is capability-agnostic (Qwen3.5-9B matches Claude Opus gains), while harness-benefit is non-monotonic (mid-tier models benefit most).
arXiv paper on autonomous agentic data engineering for model specialization. GPT-5.2 constructs a training curriculum improving a student model by 57.29% through iterative, agent-driven data adaptation. Formalizes a novel task evaluating LLMs as autonomous data engineers.
MAVEN is a lightweight symbolic reasoning scaffold to improve generalization of LLM agents in tool-calling tasks. Evaluated on BFCL v3, TauBench, Tau2Bench, AceBench and a new MAVEN-Bench benchmark, it increases GPT-OSS-120b accuracy from 48% to 71% without additional training, at roughly 1/10 the cost of proprietary baselines.
GRiD, a diffusion-model framework, generates graph-like rules for knowledge graph reasoning. Combines supervised pre-training and reinforcement learning to discover complex rules (cycles, branches) beyond simple chains. Evaluated on 6 benchmarks with open-source code.
Study of global narrative dominance in LLMs via CulturalNB, a dataset of 717 Bengali cultural instances with parallel English-Bangla question-answer pairs. Evaluation of 9 LLMs shows English questions increase global substitution and reduce local perspective coverage, even with local evidence provided.
Method to automatically generate fine-grained evaluation rubrics without human annotation, tested on four benchmarks. Training-free approach, then iterative fine-tuning via meta-judge reward signals. A fine-tuned 14B rubric generator outperforms larger proprietary models.
Study on LLM teams playing ChGK (collective reasoning quiz). Three strategies tested: Voting, Silent Team (captain observes answers), Talkative Team (captain observes answers + rationales). On 572 questions from 2025, teams outperform single models (+20 points). Best team: 44.23% accuracy, approaching human performance. Sharing rationales mitigates errors.
New post-training method for reasoning models: Feedback Distillation trains the model to match its own distribution conditioned on LLM-generated feedback at token level. Tested on Lean4 theorem-proving, it maintains greater trajectory diversity than GRPO, improves policy entropy and pass@k scaling. Combined with GRPO, it outperforms either method alone.
UniScale unifies model routing and test-time scaling (TTS) in a single optimization space to balance LLM inference quality and computational cost. The framework uses LinUCB and contextual multi-armed bandit theory to learn adaptive inference policies online, with cost modeling and efficiency-aware learning.
Study of gender-specific neurons in language models (feminine, masculine, gender-neutral). Authors propose neuron-level intervention method to identify and control gendered language generation. Experiments on two open-source LMs show gender neurons concentrate in early layers. Code and datasets released.
FAM-Bench is a 2500-instance multimodal benchmark verified by nutrition experts, evaluating Food-as-Medicine reasoning across 13 health conditions. Two tasks: assess dish suitability for a condition (image + ingredients) and rank 4 dishes by clinical relevance. Tests integration of nutritional constraints, visual cues, and ingredient evidence.
AutoSci is a memory-centric multi-agent system automating the full scientific research lifecycle. It combines SciMem (structured memory), SciFlow (5-stage execution), SciDAG (multi-agent operators), and SciEvolve (continuous learning). Code available on GitHub.
NumLeak measures memorization of public benchmarks in frontier LLMs. Models recall Fama-French data (r=0.97-0.99), US unemployment, and NOAA temperature with high fidelity. On recent unseen data, parse rate drops to 21-57% but r stays ~0.99 for answered months. A one-line system-prompt defense blocks 99.8% of attacks.
DisjunctiveNet introduces a neuro-symbolic framework to embed hard mixed-integer linear constraints and logical rules directly into neural networks using differentiable optimization layers. Through hierarchical convex relaxations, the approach ensures exact rule satisfaction while maintaining strong predictive performance on real-world datasets.
Theoretical study of padded transformer expressivity. Authors prove polynomially padded constant-precision transformers are equivalent to L-uniform AC⁰, while growing-precision ones achieve L-uniform TC⁰. Model depth and numeric precision are key factors; width beyond logarithmic does not increase expressivity.
Untrained neural networks match early visual cortex better than trained networks. Study on 720 THINGS images and fMRI from 3 subjects shows one training epoch reduces V1 alignment by 25-90% depending on learning rule. Backpropagation degrades most (Δr = -0.080), while predictive coding and STDP preserve alignment better (Δr ~ -0.04).
First model extraction attack targeting graph neural networks exploiting explainability interfaces. Method uses binary explanation masks and Monte Carlo edge sensitivity estimation to bypass strict black-box constraints. Code released on GitHub.
Vercel Blob now supports OIDC authentication as default for new projects. Vercel-issued OIDC tokens are short-lived and auto-rotating, eliminating the need for long-lived tokens. Vercel Functions and CLI automatically receive the token.
Vercel AI Chat SDK adds support for Lark and Feishu via a new official vendor adapter. Bots can post, edit, and delete messages, stream replies via Lark's native cardkit typewriter API, send interactive cards, and react with emojis. Connection uses Lark's WebSocket transport without requiring HTTP webhook exposure.
ComfyUI is a modular GUI for diffusion models with a node/graph-based interface, providing API and backend capabilities for image generation.
PolyRange is a cybersecurity AI benchmark that dynamically generates fresh web targets for each evaluation, eliminating training corpus contamination. The author addresses consensus from labs (Anthropic, OpenAI, DeepMind): static benchmarks are saturated and real-world defenses are missing. MIT-licensed, independent from the author's commercial project.
MiniMax M3, MiniMax's first model with 1M-token context window and native multimodality, is now available on Vercel AI Gateway. M3 excels at software engineering, terminal-based tool use, and agentic web browsing, optimized for multi-turn collaboration.
Mudler releases APEX GGUF quantizations of Qwen3.6-35B-A3B-Claude-4.7-Opus-Reasoning-Distilled with bundled MTP (multi-token prediction) head. Files enable self-speculative decoding via llama.cpp without separate draft model. Size +2.5% vs non-MTP version, MTP head quantized Q8_0 for high draft accuracy.
Anthropic publishes detailed documentation on sandboxing techniques across Claude.ai, Claude Code, and Cowork. Uses gVisor (Claude.ai), Seatbelt/Bubblewrap (Claude Code local), and full VMs (Cowork). Includes process sandboxes, filesystem boundaries, and egress controls to prevent credential exfiltration.
NVIDIA quantized Alibaba's Qwen3.6-35B-A3B model to NVFP4 (4-bit) using Model Optimizer. Weight reduction from 16 to 4 bits per parameter cuts GPU memory and disk size by ~3.06x. Benchmark results show minimal accuracy loss: MMLU Pro 85.6→85.0, GPQA Diamond 84.9→84.8.
OpenRouter raises $113M Series B. The LLM API aggregation platform strengthens funding to expand model offerings and infrastructure capabilities.
Large-scale study (208,000 participants, 26 million responses) reveals that training making language models helpful weakens their ability to replicate human behavior. The effect worsens with each model generation. Demographic profiles (persona trick) provide no meaningful benefit for individual predictions.
OpenAI deploys Codex on Windows 11 with 'Computer Use' feature enabling AI to autonomously control programs, test applications, and detect bugs. ChatGPT mobile app allows users to launch and monitor these tasks remotely.
Anthropic raises $65 billion in Series H funding, reaching a $965 billion valuation. No European public funds participated in the funding round.
Claude Code is an agentic coding tool in the terminal that understands your codebase and executes routine tasks, explains complex code, and handles git workflows through natural language commands.