🧑‍🔬 Vinija Jain

🏛️ Affiliations

🎓Stanford UniversityStanford · United States2021–2026 · 40 paperscurrent🏢AmazonSeattle · United States2023–2026 · 13 paperscurrent🏢GoogleMountain View · United States2025–2026 · 11 paperscurrent🏢MetaMenlo Park · United States2024–2026 · 5 paperscurrent🏢Horizon ResearchChapel Hill · United States2026 · 1 papercurrent🎓Northeastern UniversityBoston · United States2026 · 1 papercurrent

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.

📅 Works by year

2020s

📄 Papers

The most cited first (OpenAlex and our library).

1. A Comprehensive Survey of Hallucination Mitigation Techniques in Large Language Models (2024 · 249 citations)
   Large language models often produce fluent statements that sound factual but have no grounding. This "hallucination" problem is a major obstacle to using them in sensitive settings such as medicine, law, finance and customer support. The authors survey more than thirty-two mitigation methods and arrange them in a…
2. PHAnToM: Persona-based Prompting Has An Effect on Theory-of-Mind Reasoning in Large Language Models (2024 · 13 citations)
   The paper asks whether role-play prompts that give an LLM a personality change how well it handles Theory-of-Mind (ToM) reasoning, meaning inferring other agents' beliefs and knowledge.
3. Linear Probes Detect Task Format, Not Reasoning Mode in Language Model Hidden States (2026)
   Interpretability research often takes high linear-probe accuracy on hidden states as a sign that LLMs develop distinct internal encodings for each of the three reasoning types (deduction, induction and abduction).

All works

4 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 Comprehensive Survey of Hallucination Mitigation Techniques in Large Language ModelsarXiv:2401.01313S.M Towhidul Islam Tonmoy, S M Mehedi Zaman, Vinija Jain, et al.2024 · 249 citations
2. A Comprehensive Survey of Hallucination in Large Language, Image, Video and Audio Foundation Models ↗Findings of the Association for Computational Linguistics: EMNLP 2024 · no summary yetPranab Sahoo et al.2024 · 108 citations
3. PHAnToM: Persona-based Prompting Has An Effect on Theory-of-Mind Reasoning in Large Language ModelsarXiv:2403.02246Fiona Anting Tan, Gerard Christopher Yeo, Kokil Jaidka, et al.2024 · 13 citations
4. Linear Probes Detect Task Format, Not Reasoning Mode in Language Model Hidden StatesWorkshop on Trustworthy NLPSubramanyam Sahoo, Vinija Jain, Aman Chadha, et al.2026

🤝 Co-authors here

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

• Aman Chadha ×3
• Amitava Das
• Anku Rani
• S M Mehedi Zaman
• S.M Towhidul Islam Tonmoy
• See-Kiong Ng
• Vipula Rawte
• Weijie Xu
• Yang Liu

Venues

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

• Workshop on Trustworthy NLP: Workshop on Trustworthy NLP 2026
• Findings of the Association for Computational Linguistics: EMNLP 2024

🔗 Cited by

Papers of our library cite their works 189 times (of the 149,439 papers whose bibliographies we read); 31 citing papers with a page here →.

Updated 1 November 2026

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