Papers by Ruidong Liu
Open Relation Extraction: Relational Knowledge Transfer from Supervised Data to Unsupervised Data (D19-1)
Copied to clipboard
| Challenge: | Existing methods to extract relational facts from open domain corpora are time-consuming and human-intensive. |
| Approach: | They propose a framework to learn similarity metrics of relations from labeled data . they propose to transfer relational knowledge to identify novel relations in unlabeled data. |
| Outcome: | Experiments on two real-world datasets show that the proposed framework improves compared with state-of-the-art methods. |
Detecting LLM-Assisted Cheating on Open-Ended Writing Tasks on Language Proficiency Tests (2024.emnlp-industry)
Copied to clipboard
| Challenge: | Large Language Models (LLMs) have been used for open-ended writing tasks . however, there are limitations in detecting LLM-generated samples . |
| Approach: | They propose a framework for training LLM-generated text detectors that can detect LLM generated samples after being copy-typed. |
| Outcome: | The proposed model outperforms the transformer-based classifier on a high-stakes online English proficiency test. |
Synapse: Empowering LLM Agents with Episodic-Semantic Memory via Spreading Activation (2026.findings-acl)
Copied to clipboard
Hanqi Jiang, Junhao Chen, Yi Pan, Ling Chen, Weihang You, Yifan Zhou, Ruidong Zhang, Yohannes Abate, Tianming Liu
| Challenge: | Large Language Models excel at generalized reasoning, but lack the ability to accumulate experiences and maintain narrative coherence over long horizons. |
| Approach: | They propose a unified memory architecture that transcends static vector similarity. |
| Outcome: | The proposed model outperforms state-of-the-art methods in temporal and multihop reasoning tasks. |