Papers by Pengcheng Zheng

2 papers
Lightweight LLM Agent Memory with Small Language Models (2026.acl-long)

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Challenge: Existing external memory systems for LLMs have low online overhead but are unstable in accumulating latency over long interactions.
Approach: They propose a lightweight memory system for better agent memory driven by Small Language Models . lightmem modularizes memory retrieval, writing, and long-term consolidation . they show consistent gains across model scales and high efficiency .
Outcome: The proposed system improves agent memory but has low latency and low online overhead . it separates online processing from offline consolidation to enable efficient memory invocation . the proposed system achieves an average F1 improvement of 2.5 over A-MEM on LoCoMo .
CaDRL: Document-level Relation Extraction via Context-aware Differentiable Rule Learning (2025.coling-main)

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Challenge: Existing methods for document-level relation extraction (DocRE) lack logic and transparency.
Approach: They propose a Context-aware differentiable rule learning framework that learns the doc-specific logical rule to avoid suboptimal constraints.
Outcome: The proposed framework outperforms existing rule-based frameworks on three DocRE datasets.

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