6 papers
ESCRAG-R1: Retrieval-Augmented Reinforcement Learning for Emotional Support Conversation
Weichu Liu, Yuxuan Hu, Yirong Sun +6
Emotional Support Conversation (ESC) systems aim to provide holistic support by balancing professional therapeutic competence with natural empathy. However, existing methods strugg…
RAIE: Region-Aware Incremental Preference Editing with LoRA for LLM-based Recommendation
Jin Zeng, Yupeng Qi, Hui Li +4
Large language models (LLMs) are increasingly adopted as the backbone of recommender systems. However, user-item interactions in real-world scenarios are non-stationary, making pre…
Emotion and Intention Guided Multi-Modal Learning for Sticker Response Selection
Yuxuan Hu, Jian Chen, Yuhao Wang +6
Stickers are widely used in online communication to convey emotions and implicit intentions. The Sticker Response Selection (SRS) task aims to select the most contextually appropri…
LongEmotion: Measuring Emotional Intelligence of Large Language Models in Long-Context Interaction
Weichu Liu, Jing Xiong, Yuxuan Hu +10
Large language models (LLMs) have made significant progress in Emotional Intelligence (EI) and long-context modeling. However, existing benchmarks often overlook the fact that emot…
CTR-Sink: Attention Sink for Language Models in Click-Through Rate Prediction
Zixuan Li, Binzong Geng, Jing Xiong +11
Click-Through Rate (CTR) prediction, a core task in recommendation systems, estimates user click likelihood using historical behavioral data. Modeling user behavior sequences as te…
UncertaintyRAG: Span-Level Uncertainty Enhanced Long-Context Modeling for Retrieval-Augmented Generation
Zixuan Li, Jing Xiong, Fanghua Ye +9
We present UncertaintyRAG, a novel approach for long-context Retrieval-Augmented Generation (RAG) that utilizes Signal-to-Noise Ratio (SNR)-based span uncertainty to estimate simil…