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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: 3 Search mode: keyword Shortlist (0) RSS

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Do Phone-Use Agents Respect Your Privacy?

Zhengyang Tang, Ke Ji, Xidong Wang, Zihan Ye, Xinyuan Wang, Yiduo Guo · Apr 1, 2026

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 100% High protocol signal Freshness: Warm Status: Ready
Pairwise Preference Automatic Metrics Coding
  • We study whether phone-use agents respect privacy while completing benign mobile tasks.
  • To make this question measurable, we introduce MyPhoneBench, a verifiable evaluation framework for privacy behavior in mobile agents.
Open paper
Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 98% Moderate protocol signal Freshness: Cold Status: Ready
Pairwise Preference Llm As Judge Coding
  • However, building a benchmark for LLM-generated web apps remains challenging due to the need for real-world user requirements, generalizable evaluation metrics without relying on ground-truth implementations or test cases, and interpretable…
  • To address these challenges, we introduce WebCoderBench, the first real-world-collected, generalizable, and interpretable benchmark for web app generation.
Open paper
EasyAnimate: High-Performance Video Generation Framework with Hybrid Windows Attention and Reward Backpropagation

Jiaqi Xu, Kunzhe Huang, Xinyi Zou, Yunkuo Chen, Bo Liu, MengLi Cheng · May 29, 2024

Citations: 0

Match reason: Keyword overlap 1/1 across title and protocol fields.

Score: 98% Moderate protocol signal Freshness: Cold Status: Fallback
Pairwise Preference Human Eval Coding
  • To enhance video generation quality, we optimize EasyAnimate using reward backpropagation to better align with human preferences.
  • The EasyAnimate achieves state-of-the-art performance on both the VBench leaderboard and human evaluation.
Open paper

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