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Human Feedback and Eval Paper Explorer

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Total papers: 2 Search mode: keyword Shortlist (0) RSS

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HyperMem: Hypergraph Memory for Long-Term Conversations

Juwei Yue, Chuanrui Hu, Jiawei Sheng, Zuyi Zhou, Wenyuan Zhang, Tingwen Liu · Apr 9, 2026

Citations: 0

Match reason: Matches selected tags (Automatic Metrics, Pairwise Preference).

Score: 58% Moderate protocol signal Freshness: Warm Status: Ready
Pairwise Preference Llm As JudgeAutomatic Metrics General
  • Long-term memory is essential for conversational agents to maintain coherence, track persistent tasks, and provide personalized interactions across extended dialogues.
  • Experiments on the LoCoMo benchmark show that HyperMem achieves state-of-the-art performance with 92.73% LLM-as-a-judge accuracy, demonstrating the effectiveness of HyperMem for long-term conversations.
Open paper
Blinded Radiologist and LLM-Based Evaluation of LLM-Generated Japanese Translations of Chest CT Reports: Comparative Study

Yosuke Yamagishi, Atsushi Takamatsu, Yasunori Hamaguchi, Tomohiro Kikuchi, Shouhei Hanaoka, Takeharu Yoshikawa · Apr 2, 2026

Citations: 0

Match reason: Matches selected tags (Automatic Metrics, Pairwise Preference).

Score: 58% Moderate protocol signal Freshness: Warm Status: Ready
Pairwise Preference Llm As JudgeAutomatic Metrics MedicineMultilingual
  • A board-certified radiologist and a radiology resident independently performed blinded pairwise evaluations across 4 criteria: terminology accuracy, readability, overall quality, and radiologist-style authenticity.
  • Radiologist 2 rated readability as equivalent in 75% of cases and favored the human-edited translation for overall quality (40% vs 21%).
Open paper

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