🧑‍🔬 Tianqing Fang

🏛️ Affiliations

🎓Hong Kong University of Science and TechnologyHong Kong · China2019–2026 · 78 paperscurrent🏢TencentShenzhen · China2024–2026 · 35 paperscurrent🎓The Hong Kong University of Science and Technology (Guangzhou)Guangzhou · China2022–2026 · 5 paperscurrent🎓Renmin University of ChinaBeijing · China2026 · 3 paperscurrent🎓University of Hong KongPok Fu Lam · China2021–2026 · 2 paperscurrent🔬HKUST Shenzhen Research InstituteNanshan · China2026 · 1 papercurrent🏢Alibaba GroupHangzhou · China2020–2021 · 7 papers🏢KuaishouBeijing · China2023–2024 · 3 papers🎓Chinese University of Hong KongHong Kong · China2025 · 2 papers🔬Zhejiang LabHangzhou · China2020–2021 · 2 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 2 more institutions on single bylines are not listed.

🧭 Fields, topics and concepts

Of its works in our library, with the number of works on each.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. Exploring the Potential of ChatGPT on Sentence Level Relations: A Focus on Temporal, Causal, and Discourse Relations (2024 · 92 citations)
   The paper asks whether ChatGPT grasps relations that hold between sentences, which require more than surface-level reading.
2. OpenWebVoyager: Building Multimodal Web Agents via Iterative Real-World Exploration, Feedback and Optimization (2025 · 18 citations)
   Open-source models that improve themselves through exploration have so far been mostly text-only and trained in synthetic environments, where success is easy to measure.
3. Attention Entropy is a Key Factor: An Analysis of Parallel Context Encoding with Full-attention-based Pre-trained Language Models (2025 · 14 citations)
   The paper asks whether full-attention decoder-only LLMs can encode context in parallel without any fine-tuning.
4. WebEvolver: Enhancing Web Agent Self-Improvement with Co-evolving World Model (2025 · 11 citations)
   Web agents that improve by fine-tuning on their own sampled trajectories tend to plateau. They explore too little, and they underuse the web knowledge already present in pretrained LLMs. WebEvolver tackles this by training a world model alongside the agent. The world model is an LLM fine-tuned on collected…
5. Inference-Time Scaling of Verification: Self-Evolving Deep Research Agents via Test-Time Rubric-Guided Verification (2026 · 4 citations)
   Deep Research Agents (DRAs) often give unreliable answers because of wrong actions, failed tool calls or hallucinations.
6. WebAggregator: Enhancing Compositional Reasoning Capabilities of Deep Research Agent Foundation Models (2026 · 1 citation)
   Deep Research agents need more than retrieval. They must combine scattered, heterogeneous evidence through multi-step reasoning. Existing training and evaluation resources mostly reward locating a single entity, so agents learn to call tools often instead of reasoning carefully.
7. WebRollback: Enhancing Web Agents with Explicit Rollback Mechanisms (2026 · 1 citation)
   Most LLM-based web agents navigate greedily in a single direction. On live, changing websites they can enter a wrong state and waste many steps before recovering, if they recover at all. Parallel search methods are costly here because each branch needs its own browser environment. Best-first search, as in Koh et al.…
8. Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI Grounding (2026)
   GUI grounding means turning a natural-language instruction into exact click coordinates on a screenshot. MLLMs find it hard on high-resolution, crowded interfaces: they often understand the request but miss the precise pixel location. Drawing several samples raises Pass@k. However, clustering-style self-consistency…

All works

9 works of theirs in our library, the most cited first; 8 with a page here, the others link their original until we summarise them.

1. Probing Toxic Content in Large Pre-Trained Language Models ↗Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) · no summary yetNedjma Ousidhoum et al.2021 · 120 citations
2. Exploring the Potential of ChatGPT on Sentence Level Relations: A Focus on Temporal, Causal, and Discourse RelationsFindings of the Association for Computational LinguisticsChunkit Chan, Cheng Jiayang, Weiqi Wang, et al.2024 · 92 citations
3. OpenWebVoyager: Building Multimodal Web Agents via Iterative Real-World Exploration, Feedback and OptimizationAnnual Meeting of the Association for Computational Linguistics (ACL)Hongliang He, Wenlin Yao, Kaixin Ma, et al.2025 · 18 citations
4. Attention Entropy is a Key Factor: An Analysis of Parallel Context Encoding with Full-attention-based Pre-trained Language ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Zhisong Zhang, Yan Wang, Xinting Huang, et al.2025 · 14 citations
5. WebEvolver: Enhancing Web Agent Self-Improvement with Co-evolving World ModelConference on Empirical Methods in Natural Language Processing (EMNLP)Tianqing Fang, Hongming Zhang, Zhisong Zhang, et al.2025 · 11 citations
6. Inference-Time Scaling of Verification: Self-Evolving Deep Research Agents via Test-Time Rubric-Guided VerificationFindings of the Association for Computational LinguisticsYuxuan Wan, Tianqing Fang, Zaitang LI, et al.2026 · 4 citations
7. WebAggregator: Enhancing Compositional Reasoning Capabilities of Deep Research Agent Foundation ModelsAnnual Meeting of the Association for Computational Linguistics (ACL)Rui Wang, Ce Zhang, Jun-Yu Ma, et al.2026 · 1 citation
8. WebRollback: Enhancing Web Agents with Explicit Rollback MechanismsConference of the European Chapter of the Association for Computational Linguistics (EACL)Zhisong Zhang, Tianqing Fang, Kaixin Ma, et al.2026 · 1 citation
9. Measure Twice, Click Once: Co-evolving Proposer and Visual Critic via Reinforcement Learning for GUI GroundingAnnual Meeting of the Association for Computational Linguistics (ACL)Wenkai Wang, Xiyun Li, Hongcan Guo, et al.2026

🤝 Co-authors here

12 of 29 co-authors with a page, the most papers together first.

• Dong Yu ×7
• Haitao Mi ×5
• Hongming Zhang ×5
• Wenhao Yu ×4
• Zhisong Zhang ×4
• Kaixin Ma ×3
• Boyang Xue
• Cheng Jiayang
• Chenlong Deng
• Chunkit Chan
• Hongliang He
• Hongru Wang

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

• Annual Meeting of the Association for Computational Linguistics (ACL) ×4: ACL 2026 ×2, ACL 2025 ×2
• Findings of the Association for Computational Linguistics ×2: Findings of the Association for Computational Linguistics 2026, Findings of the Association for Computational Linguistics 2024
• Conference of the European Chapter of the Association for Computational Linguistics (EACL): EACL 2026
• Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2025
• Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)

🔗 Cited by

Papers of our library cite their works 178 times (of the 149,439 papers whose bibliographies we read); 47 citing papers with a page here →.

Updated 1 November 2026

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