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Human Feedback and Eval Paper Explorer

A focused feed for RLHF, preference data, rater protocols, agent evaluation, and LLM-as-judge research. Every paper includes structured metadata for quick triage.

Total papers: 43 Search mode: keyword RSS

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What Matters For Safety Alignment?

Xing Li, Hui-Ling Zhen, Lihao Yin, Xianzhi Yu, Zhenhua Dong, Mingxuan Yuan · Jan 7, 2026

Citations: 0
Red Team Automatic Metrics Tool Use General
  • This paper presents a comprehensive empirical study on the safety alignment capabilities.
  • We evaluate what matters for safety alignment in LLMs and LRMs to provide essential insights for developing more secure and reliable AI systems.
World Simulation with Video Foundation Models for Physical AI

NVIDIA, :, Arslan Ali, Junjie Bai, Maciej Bala, Yogesh Balaji · Oct 28, 2025

Citations: 0
Simulation Env Long Horizon CodingMultilingual
  • These capabilities enable more reliable synthetic data generation, policy evaluation, and closed-loop simulation for robotics and autonomous systems.
  • To accelerate research and deployment in Physical AI, we release source code, pretrained checkpoints, and curated benchmarks under the NVIDIA Open Model License at https://github.com/nvidia-cosmos/cosmos-predict2.5 and https://github.com/nv

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