# RESCUE-BENCH：面向关系感知多方情感支持对话系统的基准

- 来源：HuggingFace Daily Papers（社区热门论文）
- 发布时间：2026-09-09 08:00
- AIHOT 分数：37
- AIHOT 链接：https://aihot.news/items/cmtuxuyrr0igbrorp5u7qhc5t
- 原文链接：https://arxiv.org/abs/2609.09657

## AI 摘要

研究者构建了 RESCUE 基准，用于评估 LLM 能否捕捉并利用多方场景中不断变化的人际关系来提供情感支持。该基准取自真实情侣与家庭访谈对话，包含 191 个样本、7,079 个标注对话轮和 1,064.8 分钟视频，定义了六项任务，覆盖关系理解与关系敏感支持两类核心能力。

## 正文

Existing emotional support conversation systems mainly focus on one-on-one seeker-supporter interactions and individual emotional states, leaving interpersonal relations in multi-party scenarios underexplored. In this work, we introduce relation-aware emotional support conversation, a new task that evaluates whether LLMs can capture and utilize the evolving dynamics of relationships to offer more effective emotional support. We construct RESCUE (Relation-aware Emotional Support Conversation Understanding and Evaluation Benchmark) from real couple and family interview conversations, containing 191 samples, 7,079 annotated turns, and 1,064.8 minutes of video. Based on rich annotations of socio-emotional and support-related dynamics, RESCUE defines six tasks that evaluate two core capabilities required for relation-aware emotional support: Relational Understanding and Relation-Sensitive Support. Experiments with ten LLMs show that current models perform relatively well on tasks relying on local emotional or intervention cues, but struggle with relation-intensive tasks such as relation pattern prediction, viewpoint prediction, and support strategy prediction. These findings reveal the limitations of current LLMs in modeling interpersonal relations and making relation-sensitive support decisions.