945 articles tagged with Benchmark
Deep research agents are Large Language Model (LLM)-based systems designed for autonomous, multi-step scientific reasoning, and they hold immense potential for accelerating researc...
Anthropic's Claude Fable 5 launches at twice the Opus price, doubles FrontierCode benchmark scores, and demonstrates unsolicited tool-building behavior that marks a shift toward au...
Gemini-SQL2, présenté par Google Research, atteint 80,04 % sur le benchmark BIRD en text-to-SQL, contre 72,8 % pour OpenAI et 70,9 % pour Anthropic, selon The Decoder.Concrètement,...
Held at the prestigious Oriental Hotel, Victoria Island, Lagos, on Friday, 5 June 2026, MarkHack 5.0 unfolded as a defining gathering for Africa’s marketing, media, and technology ...
When a free open-source model becomes the on-device ASR benchmark, you have to earn your price tag. Here's what happened when we tested Speechmatics vs Whisper. https://hackernoon....
"Every Eval Ever: A Unifying Schema and Community Repository for AI Evaluation Results"We introduce Every Eval Ever, the first shared schema and community-crowdsourced repository f...
As the AI industry gradually builds standardization guidelines and systems, such as those overseen by the Tokenonmics Foundation, the need The post We’ve been measuring AI wrong; w...
A look at the structural improvements in version 1.9.0 — and why an MIT-licensed red teaming...
I wanted to know which AI notetaker transcribes most accurately — Granola, Fathom, or Otter. So I did...
Everyone wants a smooth, reliable AI agent, but the reality of building a local engine is… messy....
Current benchmarks for computer-use agents evaluate models in impersonal environments. This leaves a gap between evaluation and deployment where personal assistants are expected to...
How embedding models, chunking, retrieval modes, and query phrasing jointly determine Code-RAG quality.
Anthropic's Fable 5 was the most capable AI model ever released, topping every major benchmark and beating OpenAI's GPT 5.5 by double-digit margins on coding tests. Then the US gov...
【olmo-eval: モデル開発ループのための評価ワークベンチ】https://huggingface.co/blog/allenai/olmo-eval※AI生成の自動投稿（見出し＋リンク）#AI #生成AI #LLM #AIGenerated
🤖 [Hugging Face] olmo-eval: Stanowisko ewaluacyjne dla pętli rozwoju modelu🔗 Więcej: https://huggingface.co/blog/allenai/olmo-eval#AI #SztucznaInteligencja #TechNews #HuggingFace #...
AI agents have fundamentally changed the complexity of inference workloads. Until now, the industry has struggled to define a standard for measuring how...
Practical notes for running NVIDIA DiffusionGemma 26B A4B NVFP4 on vLLM with benchmark results on NVIDIA GB10
【VAKRAの内部構造：エージェントの推論、ツールの使用、および障害モード】https://huggingface.co/blog/ibm-research/vakra-benchmark-analysis※AI生成の自動投稿（見出し＋リンク）#AI #生成AI #LLM #AIGenerated
InferBench update ⚡ one-click benchmark for local LLM engines — TTFT, tok/s, VRAM & quality, measured for real. Now it also generates images locally via stable-diffusion.cpp, plus ...
Building trustworthy medical multimodal large language models (MLLMs) is critical for reliable clinical decision support. Existing medical hallucination benchmarks mainly focus on ...
Online group chats are social spaces with local conversational norms that are rarely stated explicitly. The ability and willingness of LLM-based agents to recognize and adapt to th...
We introduce the Massive Video Embedding Benchmark (MVEB), a 23-task benchmark for video embeddings spanning classification, zero-shot classification, clustering, pair classificati...
【Open ASRリーダーボード：新しい多言語トラックと長尺トラックによるトレンドとインサイト】https://huggingface.co/blog/open-asr-leaderboard※AI生成の自動投稿（見出し＋リンク）#AI #生成AI #LLM #AIGenerated