Pengyue Jia

Beyond Retrieval: Evidence Access and Event Aggregation in Agent Memory

Recall Begets Recall: Recurrent Memory Ranking for Personalized LLMs

Memory ranking is the stage in personalized Large Language Models (LLMs) that decides which of the candidate memories returned by a retriever enter the limited context, so that the answer is grounded in the right parts of the user's history. Existing memory rankers operate in a single pass, scoring each candidate once...

Memory Type Varies: Empowering LLM Agents for Long-Term Memory with Diverse Strategies

This work proposes a novel memory framework, named MemoType, which can adaptively recognize each memory and query type with the learned router model, and proposes a novel retrieval framework, named MemoType, which can adaptively recognize each memory and query type with the learned router model.

ProEchoMem: Enhancing Long Video Understanding via Multi-Trace Probe-Echo Memory

Inspired by Multiple-Trace Theory in cognitive psychology, this work revisit long video understanding from a probe-echo perspective, in which human episodic memories are activated and integrated in parallel, and proposes ProEchoMem, a cognitive-inspired framework that simulates the probe-echo mechanism.

Learning a Single Token to Replace Long System Prompts in LLMs

A lightweight training framework that learns a single Behavior-Equivalent Token that substantially reduces inference cost and frees nearly the entire context window for user inputs and model outputs.