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Xiangkun Hu

18 papers · 2018–2025 · 7 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

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+6 more ↓ πŸ—ΊοΈ Taxonomy Completionist (36) πŸƒ Academic Marathon Β· Sprint 🌍 Conference Polyglot Β· Silver πŸŒ‰ Interdisciplinary Bridge Β· Silver 🐣 Hot Topic Early Bird
🧭 Keyword Pioneer 🀝 Dynamic Duo (14) ⚑ Prolific Year Β· Productive ❓ The Questioner πŸ’Ž Century Club Β· Bronze πŸ—ƒοΈ Keyword Collector (98)

Papers

Common Learning Constraints Alter Interpretations of Direct Preference Optimization AISTATS 2025 DeepResearcher: Scaling Deep Research via Reinforcement Learning in Real-world Environments EMNLP 2025 Explicit Preference Optimization: No Need for an Implicit Reward Model ICML 2025 Multi-Document Event Extraction Using Large and Small Language Models EMNLP 2025 NovelQA: Benchmarking Question Answering on Documents Exceeding 200K Tokens ICLR 2025 PerSphere: A Comprehensive Framework for Multi-Faceted Perspective Retrieval and Summarization ACL 2025 Can Language Models Learn to Skip Steps? NeurIPS 2024 Knowledge-Centric Hallucination Detection EMNLP 2024 RAGChecker: A Fine-grained Framework for Diagnosing Retrieval-Augmented Generation NeurIPS 2024 Synergetic Event Understanding: A Collaborative Approach to Cross-Document Event Coreference Resolution with Large Language Models ACL 2024 An AMR-based Link Prediction Approach for Document-level Event Argument Extraction ACL 2023 Dual Cache for Long Document Neural Coreference Resolution ACL 2023 Evaluating Open-QA Evaluation NeurIPS 2023 Exploiting Abstract Meaning Representation for Open-Domain Question Answering ACL 2023 Plan, Verify and Switch: Integrated Reasoning with Diverse X-of-Thoughts EMNLP 2023 Dialogue Meaning Representation for Task-Oriented Dialogue Systems EMNLP 2022 RLET: A Reinforcement Learning Based Approach for Explainable QA with Entailment Trees EMNLP 2022 Incorporating Argument-Level Interactions for Persuasion Comments Evaluation using Co-attention Model COLING 2018