1 citations · 1 across the 4 of their papers we have counts for
4 papers
Towards Root Memory: Benchmarking and Enhancing Implicit Logical Memory Retrieval for Personalized LLMs
Hongxun Ding, Xiang Yu, Chengbing Wang +4
Memory systems are essential for personalized Large Language Models (LLMs). However, retrieval within these systems primarily relies on semantic similarity, potentially missing log…
AlpsBench: An LLM Personalization Benchmark for Real-Dialogue Memorization and Preference Alignment
Jianfei Xiao, Xiang Yu, Chengbing Wang +8
As Large Language Models (LLMs) evolve into lifelong AI assistants, LLM personalization has become a critical frontier. However, progress is currently bottlenecked by the absence o…
Rebalancing Contrastive Alignment with Bottlenecked Semantic Increments in Text-Video Retrieval
Jian Xiao, Zijie Song, Jialong Hu +4
Recent progress in text-video retrieval has been largely driven by contrastive learning. However, existing methods often overlook the effect of the modality gap, which causes ancho…
Text Proxy: Decomposing Retrieval from a 1-to-N Relationship into N 1-to-1 Relationships for Text-Video Retrieval
Jian Xiao, Zhenzhen Hu, Jia Li +1
Text-video retrieval (TVR) has seen substantial advancements in recent years, fueled by the utilization of pre-trained models and large language models (LLMs). Despite these advanc…