Papers by Xiaolong Weng
AnchorAlign: A Novel Anchor Alignment-enhanced Generative Method for Joint Named Entity Recognition and Relation Extraction (2026.findings-acl)
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| Challenge: | Named Entity Recognition and Relation Extraction are interdependent tasks in information extraction. |
| Approach: | They propose a generative method enhanced by anchor alignment to bridge NER and RE tasks . they use anchor entities as semantic pivots to align the two tasks based on their semantic representations . |
| Outcome: | The proposed method outperforms state-of-the-art models on five benchmark datasets. |
SR-RAG: Verifiable Multi-Hop Reasoning via On-the-fly Symbolic Graph Construction (2026.findings-acl)
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| Challenge: | Existing paradigms for multi-hop reasoning suffer from high construction costs and limited adaptability to dynamic knowledge. |
| Approach: | They propose a symbolic reasoning framework for multi-hop question answering that integrates the advantages of both paradigms by dynamically generating sub-questions, performing information retrieval and symbolic encoding based on an on-the-fly graph and using a symbol verifier to validate intermediate reasoning steps. |
| Outcome: | The proposed framework significantly improves accuracy and robustness on multiple multi-hop benchmarks and a medical dataset. |
Foot-In-The-Door: A Multi-turn Jailbreak for LLMs (2025.emnlp-main)
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| Challenge: | Large Language Models (LLMs) are increasingly integrated into real-world applications, requiring a high level of safety and alignment. |
| Approach: | They propose a multi-turn jailbreak method that leverages foot-in-the-door principles to escalate malicious intent of user queries through intermediate bridge prompts and aligns the model’s response by itself to induce toxic responses. |
| Outcome: | The proposed method achieves an average attack success rate of 94% across seven widely used models outperforming existing state-of-the-art methods. |