Papers by Jiaji Deng

2 papers
Remember Me, Refine Me: A Dynamic Procedural Memory Framework for Experience-Driven Agent Evolution (2026.findings-acl)

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Challenge: Existing frameworks treat memory as a static append-only archive . Existing systems focus on passive accumulation, resulting in a 'passive accumulation' of memory.
Approach: They propose a framework for experience-driven agent evolution that integrates procedural memory with contextual information to create a high-quality experience pool.
Outcome: Experiments on BFCL-V3 and AppWorld show that ReMe outperforms memoryless Qwen3-8B.
Ground Every Sentence: Improving Retrieval-Augmented LLMs with Interleaved Reference-Claim Generation (2025.findings-naacl)

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Challenge: Existing methods to enhance credibility and verifiability of large language models (LLMs) mainly focus on passage-level or paragraph-level references or citations, which fall short in verifikatability.
Approach: They propose a method that provides sentence-level citations in LLM-generated responses.
Outcome: The proposed method achieves 90% accuracy in long-form question-answering tasks.

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