Papers by Yuliang Yan
TimelineQA: A Benchmark for Question Answering over Timelines (2023.findings-acl)
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Wang-Chiew Tan, Jane Dwivedi-Yu, Yuliang Li, Lambert Mathias, Marzieh Saeidi, Jing Nathan Yan, Alon Halevy
| Challenge: | Existing question answering techniques for lifelogs do not provide accurate answers . augmented reality glasses have led to the creation of personal assistants . |
| Approach: | They propose to use a benchmark to query lifelogs to find out what happened in real life . they find that extractive QA systems out-perform retrieval-augmented QA techniques . |
| Outcome: | The proposed method outperforms state-of-the-art retrieval-augmented QA systems in atomic queries and multi-hop queries. |
DuFFin: A Dual-Level Fingerprinting Framework for LLMs IP Protection (2026.findings-eacl)
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| Challenge: | Large language models are valuable intellectual property due to the computational cost of training. |
| Approach: | They propose a dual-level fingerprinting framework that extracts trigger patterns and knowledge-level signatures to verify black-box ownership. |
| Outcome: | The proposed framework verifies the copyright of protected LLMs on their variants, achieving an IP-ROC greater than 0.99. |
Hallucination Detection for Generative Large Language Models by Bayesian Sequential Estimation (2023.emnlp-main)
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| Challenge: | Existing methods for detecting hallucinations require large numbers of observations to be retrieved, increasing response times. |
| Approach: | They propose a framework that leverages Bayesian sequential analysis to optimize the trade-off between costs and benefits during the hallucination detection process. |
| Outcome: | The proposed framework surpasses existing methods in efficiency and precision of hallucination detection. |
Measure Children’s Mindreading Ability with Machine Reading (2023.findings-emnlp)
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| Challenge: | Existing scoring models do not take the features of the stories and video clips into account when scoring, which will reduce the accuracy of the models. |
| Approach: | They propose to leverage the features extracted from stories and videos related to the questions being asked during the children’s mindreading evaluation. |
| Outcome: | The proposed framework agrees well with human experts on scores produced by the models. |
Route to Rome Attack: Directing LLM Routers to Expensive Models via Adversarial Suffix Optimization (2026.acl-long)
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| Challenge: | Existing routing attacks depend on white-box access or heuristic prompts, rendering them ineffective in real-world black-box scenarios. |
| Approach: | They propose a cost-aware routing strategy that routes queries to the least-cost model . they propose heuristic prompts that are ineffective in real-world black-box scenarios . |
| Outcome: | The proposed approach significantly increases the routing rate to expensive models on queries of different distributions. |