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PhD student at King’s College London researching AI for Scientific Discovery, code reproduction, and reinforcement learning for LLM-based agents.
CV
Research experience, education, publications, and teaching of Yanzheng Xiang.
Education
Education, awards, competitions, and course teaching of Yanzheng Xiang.
News
Paper acceptances and invited talks from Yanzheng Xiang.
Posts
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Blog Post number 4
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Blog Post number 1
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portfolio
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publications
A Divide-And-Conquer Approach for Multi-label Multi-hop Relation Detection in Knowledge Base QA
Published in Findings of EMNLP 2021, 2021
Divide-and-conquer strategy for multi-label, multi-hop relation detection in knowledge-base question answering.
Recommended citation: Deyu Zhou, Yanzheng Xiang, Linhai Zhang, Chenchen Ye, Qian-Wen Zhang, Yunbo Cao. 2021. "A Divide-And-Conquer Approach for Multi-label Multi-hop Relation Detection in Knowledge Base QA." In Findings of EMNLP 2021.
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G3R: A Graph-Guided Generate-and-Rerank Framework for Cross-domain Text-to-SQL Generation
Published in Findings of ACL 2023, 2023
A graph-guided generate-and-rerank framework that advances cross-domain text-to-SQL generation.
Recommended citation: Yanzheng Xiang, Qian-Wen Zhang, Xu Zhang, Zejie Liu, Yunbo Cao, Deyu Zhou. 2023. "G3R: A Graph-Guided Generate-and-Rerank Framework for Cross-domain Text-to-SQL Generation." In Findings of ACL 2023.
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Addressing Order Sensitivity of In-Context Demonstration Examples in Causal Language Models
Published in Findings of ACL 2024, 2024
Mitigating sensitivity to demonstration order in in-context learning with causal language models.
Recommended citation: Yanzheng Xiang, Hanqi Yan, Lin Gui, Yulan He. 2024. "Addressing Order Sensitivity of In-Context Demonstration Examples in Causal Language Models." In Findings of ACL 2024.
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Encourage or Inhibit Monosemanticity? Revisit Monosemanticity from a Feature Decorrelation Perspective
Published in EMNLP 2024, 2024
Analyzing how feature decorrelation influences monosemanticity in language models.
Recommended citation: Hanqi Yan, Yanzheng Xiang, Guangyi Chen, Yifei Wang, Lin Gui, Yulan He. 2024. "Encourage or Inhibit Monosemanticity? Revisit Monosemanticity from a Feature Decorrelation Perspective." In EMNLP 2024.
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The Mystery of In-Context Learning: A Comprehensive Survey on Interpretation and Analysis
Published in EMNLP 2024, 2024
Surveying interpretability and analysis techniques for understanding in-context learning.
Recommended citation: Yuxiang Zhou, Jiazheng Li, Yanzheng Xiang, Hanqi Yan, Lin Gui, Yulan He. 2024. "The Mystery of In-Context Learning: A Comprehensive Survey on Interpretation and Analysis." In EMNLP 2024.
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SciReplicate-Bench: Benchmarking LLMs in Agent-driven Algorithmic Reproduction from Research Papers
Published in COLM 2025, 2025
Benchmarking agentic LLM systems on reproducing algorithms described in research papers.
Recommended citation: Yanzheng Xiang, Hanqi Yan, Shuyin Ouyang, Lin Gui, Yulan He. 2025. "SciReplicate-Bench: Benchmarking LLMs in Agent-driven Algorithmic Reproduction from Research Papers." In COLM 2025.
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PECAN: LLM-Guided Dynamic Progress Control with Attention-Guided Hierarchical Weighted Graph for Long-Document QA
Published in Findings of ACL 2025, 2025
Dynamic progress control with hierarchical graph reasoning for long-document question answering.
Recommended citation: Xinyu Wang, Yanzheng Xiang, Lin Gui, Yulan He. 2025. "PECAN: LLM-Guided Dynamic Progress Control with Attention-Guided Hierarchical Weighted Graph for Long-Document QA." In Findings of ACL 2025.
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Stop the Flip-Flop: Context-Preserving Verification for Fast Revocable Diffusion Decoding
Published in ICML 2026, 2026
COVER accelerates revocable diffusion decoding while preserving context and generation quality.
Recommended citation: Yanzheng Xiang, Lan Wei, Yizhen Yao, Qinglin Zhu, Hanqi Yan, Chen Jin, Philip Alexander Teare, Dandan Zhang, Lin Gui, Amrutha Saseendran, Yulan He. 2026. "Stop the Flip-Flop: Context-Preserving Verification for Fast Revocable Diffusion Decoding." In ICML 2026.
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talks
Towards Automatic Code Reproduction for Scientific Papers: Benchmarks and Methodologies
Invited Talk, Meta, LLaMA Community Meet-up, London, United Kingdom, June 04, 2025
I presented our latest work on SciReplicate-Bench and shared methodologies for building agentic LLM systems that can reliably reproduce code from scientific publications. The talk covered benchmarking strategies, memory management, and tooling considerations for research automation.
teaching
Discrete Mathematics
Course teaching, Southeast University, 2021
Course teaching at Southeast University in 2021.
Computer Programming for Data Scientists
Course teaching, King's College London, 2024
Course teaching at King’s College London in 2024.