Papers by Jiejun Tan

3 papers
Small Models, Big Insights: Leveraging Slim Proxy Models To Decide When and What to Retrieve for LLMs (2024.acl-long)

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Challenge: Existing methods to determine the knowledge an LLM already possesses and the knowledge that requires the help of a search engine are expensive and require excessive computational costs.
Approach: They propose a slim proxy model that detects missing knowledge in LLMs with a proxy model and use it to perform retrieval for the missing knowledge.
Outcome: The proposed approach detects missing knowledge in LLMs with a slim proxy model and takes its answers as heuristic answers.
OmniEval: An Omnidirectional and Automatic RAG Evaluation Benchmark in Financial Domain (2025.emnlp-main)

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Challenge: a new benchmark for RAG is developed for the financial domain . omnidirectional and automatic benchmarks are difficult to build in vertical domains .
Approach: They propose an omnidirectional and automatic RAG benchmark for the financial domain . they categorize RAG scenarios by task classes and 16 financial topics .
Outcome: The proposed benchmark achieves an 87.47% acceptance ratio in human evaluations of generated instances.
Memory Matters More: Event-Centric Memory as a Logic Map for Agent Searching and Reasoning (2026.findings-acl)

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Challenge: Existing methods for storing and retrieving memory are limited by shallow semantic retrieval.
Approach: They propose a memory mechanism that organizes and retrieves past experiences to support decision-making.
Outcome: Experiments on LoCoMo and NarrativeQA show that CompassMem improves retrieval and reasoning performance across multiple backbone models.

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