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Discover the Best AI Resources

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AIAIAny

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Contents

Natural Language Processing Papers·2026
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It Takes Two to Match: Co-Evolving Generative Retriever with Reinforcement Learning

Runpeng Dai, Kaili Huang +2·University of North Carolina at Chapel Hill, Apple

Generates compact keyword sets for both queries and items with LLMs and matches them directly via an inverted index. Uses supervised fine-tuning to align keyword spaces, then alternates GRPO-based reinforcement learning on query- and item-side generators to co-evolve representations and maximize retrieval F1 while staying compatible with keyword-based infrastructure.

#retrieval#LLM#RL#sft#benchmark+2
Hugging Face
AI Model·2026
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nvidia/Qwen3.8-Flash-Next-NVFP4

NVIDIA, Qwen Team (Alibaba)

NVFP4-quantized checkpoint of Qwen3.8-Flash-Next for GPU-optimized multimodal autoregressive inference — routed MoE experts in W4A4 NVFP4 while attention/ancillary layers remain BF16; ~2.7× smaller than the BF16 source and supports very long contexts.

#qwen#nvidia#vllm#moe#multimodal+5
Hugging Face
AI Dataset·2026
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Open Yap 1K

The Agentic Data Company

Provides a dual-channel, channel-separated sample (8.9 hours) and access path to a 1,000‑hour English conversational corpus for commercial and research use. Delivers 48 kHz per-speaker audio, word-level machine transcripts, and per-speaker metadata designed for full‑duplex/turn-taking and ASR/ TTS research.

#speech#audio#ASR#stt#tts+3
Hugging Face
AI Dataset·2026
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MoreThought/Fable-5.1-Max-Reasoning-Filtered-10000x

MoreThought, Hugging Face

Provides 10,000 agentic multi-turn coding and reasoning traces from Fable 5.1 with step-by-step chain-of-thought and tool-use, heavily deduplicated and filtered; totals ~500M tokens (1.97 GB). Suited for SFT, distillation, and training long-horizon reasoning and code-generation models.

#huggingface#sft#distillation#reasoning#coding+5
Hugging Face
AI Dataset·2026
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Nemotron-RL-litmus-bench-v0.2

NVIDIA Corporation

Turns chemistry and molecular-property questions into verifiable short-answer tasks for language-model training and evaluation, with nearly 50,000 questions drawn from multiple datasets.

#chemistry#RL#datasets#training-data#evaluation+2
AI Agent Papers·2026
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Repo-To-Skill: Distilling GitHub Repositories Into AI4AI Skills

Jianlyu Chen, Yuyang Hu +9·Beijing Academy of Artificial Intelligence, University of Science and Technology of China +2

Distills operational know‑how from ML GitHub repositories into compact, verified 'skills' that research agents can load and reuse. Produces a skill format (SKILL.md, references, scripts), the AREX‑Skill Library (5,000+ skills from 1,000 repos), and demonstrates sizable benchmark gains when agents use skills.

#agent-skills#distillation#github#research#mlops+5
AI Agent Papers·2026
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EarlyEval: Cheaper Agent Evaluation via Early Outcome Prediction

Yuling Shi, Zhensu Sun +4·Shanghai Jiao Tong University, Shanghai, China, Singapore Management University, Singapore +2

Predicts an LLM agent's final success or failure from partial execution traces and halts runs when outcomes are confident to save per-task compute. Uses LightGBM success/failure classifiers on behavioral, textual, and reference features; cuts 13–26% steps and up to 44% input tokens on benchmarks.

#evaluation#benchmarks#ai-agent#llm#agent-skills
Large Language Model Papers·2026
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Verify Before You Distill: Prompt-Level Teacher Gating for On-Policy Distillation

Zhiwei Zhang, Zechen Sun +7

Selectively admits dense token-level teacher supervision only after a prompt-level verifier audit, routing prompts that fail the audit to verifier-grounded trajectory supervision instead — reducing harmful updates from confidently wrong teachers and improving teacher GPU utilization.

#distillation#rl#LLM#paper#evaluation+3
Hugging Face
AI Dataset·2026
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The First Fable 5.1 Reasoning Data

MoreThought

Contains 5,000 coding and chain-of-thought reasoning traces generated by Fable 5.1 — ~150M tokens of step-by-step programming CoT. Deduplicated and filtered for high quality; intended for supervised fine-tuning and distillation to improve reasoning in smaller models.

#huggingface#reasoning#thinking#distillation#coding+3
Hugging Face
AI Dataset·2026
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MoreThought/Fable-5.1-Max-Reasoning-Filtered-1000x

MoreThought

A curated set of 1,000 high-quality chain-of-thought coding and reasoning traces generated by Fable 5.1, totaling ~30M tokens (109 MB). Designed for SFT/distillation to teach smaller models step-by-step programmatic reasoning and debugging.

#huggingface#distillation#sft#thinking#reasoning+4
Hugging Face
AI Video·2026
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VDN-Minimax-H3

OpenVDN, MiniMax-AI

Adds a plug-and-play linear-attention branch and LoRA adapters to MiniMax-H3 to run text-to-video generation faster than real-time (near-lossless quality tradeoffs). Includes an optimized FP8 inference stack and a community license with regional restrictions.

#diffusers#safetensors#ai-video#video#fp8+5
Hugging Face
AI Dataset·2026
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TikTok Videos, 4.5 Billion

kuben-developer

Provides 4.5 billion TikTok video records with captions, timestamps, music IDs and engagement counts for research; split across 27 zstd-compressed Parquet files (~289 GB) and sampled via TikTok's mobile API; released for research-use only with privacy and ToS caveats.

#parquet#video#ai-video#huggingface#polars+2
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