…Performance benchmarking tools are valuable for inference systems. They can be used to verify that a system is operating as intended, or find the best backend for a specific enterprise system. They…
…Asymmetric Group Policy Optimization for Verifiable Reasoning and Search Ads Relevance at JD (2026) CoVerRL: Breaking the Consensus Trap in Label-Free Reasoning via Generator-Verifier Co-Evolution (2026) Please give a…
…An Interpretable Per-Dimension Accent Benchmark for Indic Text-to-Speech (2026) Language-Invariant Multilingual Speaker Verification for the TidyVoice 2026 Challenge (2026) Dual-LoRA: Parameter-Efficient Adversarial Disentanglement for Cross-Lingual…
…CoE benchmark (51K multi-hop QA with bbox annotations), and significantly outperforms text-based baselines on SlideVQA where layout matters. We hope CoE pushes RAG from information finding toward causal, verifiable visual…
I was frustrated that every coding agent (OpenCode, Cursor, Claude Code) assumes you're running GPT-5.4 or Claude Opus. If you try them with a local model like Gemma or Qwen they fall apart. I find that often tool calls …
Hi HN, I have been working on alint for the last little while. It is a linter for the shape of a repository rather than the code inside it. clippy, ruff, eslint, and others already handle the AST and code space. alint ch…
…AI-generated summary Speculative decoding speeds up autoregressive generation in Large Language Models (LLMs) through a two-step procedure, where a lightweight draft model proposes tokens which the target model then verifies…
…Reinforcement learning (RL) could overcome these limitations, but its successes have so far been concentrated in verifiable domains that rely on deterministic checkers—a luxury not available in open-ended captioning. With…
…It runs popular models across leading platforms, measures performance for a wide range of use cases and publishes results anyone can verify. Why do benchmarks like this matter? Because modern AI isn…
…It runs popular models across leading platforms, measures performance for a wide range of use cases and publishes results anyone can verify. Why do benchmarks like this matter? Because modern AI isn…
…It runs popular models across leading platforms, measures performance for a wide range of use cases and publishes results anyone can verify. Why do benchmarks like this matter? Because modern AI isn…
…It runs popular models across leading platforms, measures performance for a wide range of use cases and publishes results anyone can verify. Why do benchmarks like this matter? Because modern AI isn…
