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Fengbin Zhu

Fengbin Zhu has 4 papers in our library, in 2021–2026, most of them on Language models & pretraining, Question answering, Evaluation & benchmarks; often with Fuli Feng, Yang Zhang, Chao Wang.

4 papers in our library · 2021–2026

OpenAlex · ORCID · Wikidata · h-index 9 · 69 works · 514 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 235 times in our library · ⭐ Paper Stars ranking: #4233

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

🎓National University of SingaporeSingapore · Singapore2021–2026 · 54 papersEducation · Computer Sciencecurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 Fields, topics and concepts

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

📚 Shelves 9The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 4 worksComputer Science · 4 worksArtificial Intelligence · 4 worksLanguage and Linguistics · 4 worksMathematics · 1 workInformation Systems · 2 worksComputer Vision and Pattern Recognition · 1 workExperimental and Cognitive Psychology · 1 workPsychology · 1 work

🧭 Topics 4Research subjects and languages the work is about.Evaluation & benchmarks · 1 workQuestion answering · 1 workLanguage models & pretraining · 2 worksBias, fairness & safety · 1 work

 Works by year

2020s

20262 papers20251 paper20211 paper

 Papers

The most cited first (OpenAlex and our library).

  1. TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance (2021 · 397 citations)
    Most question answering research handles text, knowledge bases or tables separately. Real documents such as corporate financial reports mix numeric tables with prose that explains or adds to them. This paper introduces TAT-QA, a benchmark built from such reports. Each context pairs one table with at least two related…
  2. Latent Inter-User Difference Modeling for LLM Personalization (2025 · 12 citations)
    Most LLM personalization conditions generation on a user's own history. However, what makes someone distinctive is how they deviate from other people. An earlier method, DPL, asked the LLM to compare users in natural language. That comparison is hard to steer and fills the prompt with other users' raw text.
  3. PERM: Psychology-grounded Empathetic Reward Modeling for Large Language Models (2026 · 8 citations)
    LLMs used in emotionally sensitive settings often give generic or overly solution-focused replies instead of real emotional support.
  4. TROJail: Trajectory-Level Optimization for Multi-Turn Large Language Model Jailbreaks with Process Rewards (2026 · 3 citations)
    The paper addresses training automated attackers that break the safety guardrails of black-box LLMs over several dialogue turns.

 Co-authors here

11 co-authors with a page, the most papers together first.

Venues

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

 Cited by

Papers of our library cite their works 235 times (of the 149,439 papers whose bibliographies we read); 55 citing papers with a page here →.

Updated

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