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Person: "gneubig"
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claude-code gemini qwen3-coder gemini-2.5-flash exa openpipe coreweave statsig openai zed claude gemini langchain anthropic fair alibaba hud-evals agent-protocols interoperability standardization agent-evaluation coding-agents software-optimization web-browsing reinforcement-learning multi-turn-reasoning optimizer-design data-efficient-rlvr leaderboards benchmarking zeddotdev mathemagic1an hwchase17 giffmana gneubig crystalsssup sayashk _philschmid _akhaliq jaseweston
Exa raised a $700m Series B, OpenPipe was acquired by Coreweave, and Statsig and Alex were acquired by OpenAI. The Agent/Client Protocol (ACP) was introduced by the Zed team to standardize IDE-agent interoperability, supporting Claude Code and Gemini CLIs. LangChain 1.0 alpha unifies content blocks for reasoning and multimodal data. The OSWorld Verified leaderboard promotes reproducible evaluation of computer-use agents including OpenAI and Anthropic models. FAIR revealed coding agent cheating on SWE-Bench Verified. PR Arena hosts live coding agent competitions. Benchmarks like GSO and Holistic Agent Leaderboard test software optimization and web browsing tasks, with Qwen3-Coder and Gemini 2.5 Flash showing strong performance. Advances in reinforcement learning for tool use include SimpleTIR improving multi-turn tool use success rates and UI-TARS-2 advancing GUI agents. The DARLING optimizer improves quality and diversity in reasoning and instruction following, while DEPO achieves data-efficient RLVR with significant speedups.
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gpt-oss-120b gpt-oss-20b kimi-k2 deepseek-r1 qwen-3-32b openai huggingface microsoft llamaindex ollama baseten fireworksai cerebras groq together anthropic google uk-aisi sliding-window-attention mixture-of-experts rope context-length mxfp4-format synthetic-data reasoning-core-hypothesis red-teaming benchmarking coding-benchmarks model-performance fine-tuning woj_zaremba sama huybery drjimfan jxmnop scaling01 arunv30 kevinweil xikun_zhang_ jerryjliu0 ollama basetenco reach_vb gneubig shxf0072 _lewtun
OpenAI released its first open models since GPT-2, gpt-oss-120b and gpt-oss-20b, which quickly trended on Hugging Face. Microsoft supports these models via Azure AI Foundry and Windows Foundry Local. Key architectural innovations include sliding window attention, mixture of experts (MoE), a RoPE variant, and a 256k context length. The models use a new MXFP4 format supported by llama.cpp. Hypotheses suggest gpt-oss was trained on synthetic data to enhance safety and performance, supporting the Reasoning Core Hypothesis. OpenAI announced a $500K bounty for red teaming with partners including Anthropic, Google, and the UK AISI. Performance critiques highlight inconsistent benchmarking results, with GPT-OSS-120B scoring 41.8% on the Aider Polyglot coding benchmark, trailing competitors like Kimi-K2 and DeepSeek-R1. Some users note the model excels in math and reasoning but lacks common sense and practical utility.
Gemini 2.5 Pro/Flash GA, 2.5 Flash-Lite in Preview
gemini-2.5 gemini-2.5-flash-lite gemini-2.5-flash gemini-2.5-pro gemini-2.5-ultra kimi-dev-72b nanonets-ocr-s ii-medical-8b-1706 jan-nano deepseek-r1 minimax-m1 google moonshot-ai deepseek cognitivecompai kling-ai mixture-of-experts multimodality long-horizon-planning benchmarking coding-performance long-context ocr video-generation model-releases tulsee_doshi oriolvinyalsml demishassabis officiallogank _philschmid swyx sainingxie scaling01 gneubig clementdelangue mervenoyann
Gemini 2.5 models are now generally available, including the new Gemini 2.5 Flash-Lite, Flash, Pro, and Ultra variants, featuring sparse Mixture-of-Experts (MoE) transformers with native multimodal support. A detailed 30-page tech report highlights impressive long-horizon planning demonstrated by Gemini Plays Pokemon. The LiveCodeBench-Pro benchmark reveals frontier LLMs struggle with hard coding problems, while Moonshot AI open-sourced Kimi-Dev-72B, achieving state-of-the-art results on SWE-bench Verified. Smaller specialized models like Nanonets-OCR-s, II-Medical-8B-1706, and Jan-nano show competitive performance, emphasizing that bigger models are not always better. DeepSeek-r1 ties for #1 in WebDev Arena, and MiniMax-M1 sets new standards in long-context reasoning. Kling AI demonstrated video generation capabilities.
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claude-4 claude-4-opus claude-4-sonnet gemini-2.5-pro gemma-3n imagen-4-ultra anthropic google-deepmind openai codebase-understanding coding agentic-performance multimodality text-to-speech video-generation model-integration benchmarking memory-optimization cline amanrsanger ryanpgreenblatt johnschulman2 alexalbert__ nearcyan mickeyxfriedman jeremyphoward gneubig teortaxesTex scaling01 artificialanlys philschmid
Anthropic's Claude 4 models (Opus 4, Sonnet 4) demonstrate strong coding abilities, with Sonnet 4 achieving 72.7% on SWE-bench and Opus 4 at 72.5%. Claude Sonnet 4 excels in codebase understanding and is considered SOTA on large codebases. Criticism arose over Anthropic's handling of ASL-3 security requirements. Demand for Claude 4 is high, with integration into IDEs and support from Cherry Studio and FastHTML. Google DeepMind introduced Gemini 2.5 Pro Deep Think and Gemma 3n, a mobile multimodal model reducing RAM usage by nearly 3x. Google's Imagen 4 Ultra ranks third in the Artificial Analysis Image Arena, available on Vertex AI Studio. Google also promoted Google Beam, an AI video model for immersive 3D experiences, and new text-to-speech models with multi-speaker support. The GAIA benchmark shows Claude 4 Opus and Sonnet leading in agentic performance.
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grok-3 grok-3-mini gpt-4.5 claude-3.7-sonnet quasar-alpha optimus-alpha gpt-4.1 kaleidoscope internvl3 internvit qwen2.5vl transmamba fantasytalking openai alibaba cmu reinforcement-learning reasoning benchmarks vision multilinguality multimodality transformers attention-mechanisms agents code-generation model-performance rasbt sarahookr mervenoyann gneubig svpino mathemagic1an
The AI news recap highlights independent evaluations showing Grok-3 outperforming models like GPT-4.5 and Claude 3.7 Sonnet on reasoning benchmarks, while Grok-3 mini excels in reasoning tasks. Research on reinforcement learning (RL) fine-tuning reveals potential improvements for small reasoning models but also notes instability in reported gains. Benchmark results suggest Quasar Alpha and Optimus Alpha may be versions of GPT-4.1. Vision and multimodal models like Kaleidoscope, supporting 18 languages, and InternVL3, built on InternViT and Qwen2.5VL, demonstrate advances in multilingual vision and reasoning. The fusion model TransMamba combines transformer precision with speed via SSM mechanisms. Alibaba's FantasyTalking generates realistic talking portraits. Agent-focused events at CMU and tools like FilmAgent AI for virtual film production and BrowseComp benchmark for browsing agents were announced. The coding assistant Augment supports multiple IDEs with code analysis and suggestions. Discussions also covered Google’s new agent-to-agent protocol concept.