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Jiahui Geng

Jiahui Geng has 3 papers in our library, in 2025–2026, most of them on Multilingual & cross-lingual NLP, Language models & pretraining, Bias, fairness & safety; often with Bo Zeng, Chenyang Lyu, Giovanni Puccetti.

3 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 10 · 67 works · 473 citations OpenAlex, 2026-10-14

📄 3 works in our library · 🔗 Cited 211 times in our library · 6 more in our library without a page yet · ⭐ Paper Stars ranking: #8505

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

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 4 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. Shaping the Safety Boundaries: Understanding and Defending Against Jailbreaks in Large Language Models (2025 · 19 citations)
    The paper asks how jailbreak prompts get past an LLM's safety alignment. Earlier interpretability studies disagreed on which layers matter and on how malicious activations evolve. The authors argue those conflicts come from small samples, often around 100 prompts. They analyze last-token activations for more than…
  2. Is Human-Like Text Liked by Humans? Multilingual Human Detection and Preference Against AI (2026 · 5 citations)
    Earlier work suggested that people can barely tell LLM output from human writing. Most of that evidence came from English text, GPT-3.5-turbo, and small samples. This paper tests whether the claim holds for newer models, other languages and expert readers, aiming to estimate the ceiling of human detection ability.
  3. Marco-Bench-MIF: On Multilingual Instruction-Following Capability of Large Language (2025 · 5 citations)
    Most benchmarks for LLM instruction following are English-only or plain machine translations, so they handle constraints that don't transfer across languages poorly.

All works

9 works of theirs in our library, the most cited first; 3 with a page here, the others link their original until we summarise them.

  1. A Survey of Confidence Estimation and Calibration in Large Language Models ↗arXiv:2311.08298 · no summary yetJiahui Geng et al.2023 · 97 citations
  2. CVQA: Culturally-diverse Multilingual Visual Question Answering Benchmark ↗arXiv:2406.05967 · no summary yetDavid Romero et al.2024 · 90 citations
  3. A Survey of Confidence Estimation and Calibration in Large Language Models ↗Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) · no summary yetJiahui Geng et al.2024 · 84 citations
  4. Improved Gradient Inversion Attacks and Defenses in Federated Learning ↗IEEE Transactions on Big Data · no summary yetJiahui Geng et al.2023 · 51 citations
  5. A Survey on Dataset Distillation: Approaches, Applications and Future Directions ↗arXiv:2305.01975 · no summary yetJiahui Geng et al.2023 · 25 citations
  6. CaMMT: Benchmarking Culturally Aware Multimodal Machine Translation ↗Findings of the Association for Computational Linguistics: EMNLP 2025 · no summary yetEmilio Villa-Cueva et al.2025 · 5 citations

 Co-authors here

12 of 21 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 211 times (of the 149,439 papers whose bibliographies we read); 59 citing papers with a page here →.

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