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Sahil Wadhwa

Sahil Wadhwa has 2 papers in our library, in 2025–2026, most of them on Reasoning, Language models & pretraining, Bias, fairness & safety; often with Huy Nghiem.

2 papers in our library · 2025–2026

OpenAlex · ORCID · h-index 5 · 25 works · 113 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 9 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #9961

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

🏢Capital OneTysons Corner · United States2024–2026 · 12 paperscurrent🎓Stevens Institute of TechnologyHoboken · United States2026 · 1 papercurrent🎓University of Illinois Urbana-ChampaignUrbana · United States2019–2021 · 3 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.

📚 Shelves 6The field of science this work belongs to (OpenAlex fields).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 worksSocial Sciences · 1 workSociology and Political Science · 1 work

🧭 Topics 3Research subjects and languages the work is about.Reasoning · 2 worksBias, fairness & safety · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and Alignment (2025 · 9 citations)
    Conversational assistants built on LLMs need an input filter that catches fraudulent requests, illegal-activity requests and jailbreak attempts before they reach the main agent.
  2. ART: Adaptive Reasoning Trees for Explainable Claim Verification (2026 · 1 citation)
    LLMs can reach fact-checking verdicts, but their reasoning is opaque and hard to challenge. Chain-of-Thought rationales may not reflect how the model actually decided. The authors (Capital One / Stevens Institute of Technology) propose ART (Adaptive Reasoning Trees), which turns a claim into a tree of pro and con…

All works

3 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. Refining Input Guardrails: Enhancing LLM-as-a-Judge Efficiency Through Chain-of-Thought Fine-Tuning and AlignmentarXiv:2501.13080Melissa Kazemi Rad, Huy Nghiem, Andy Luo, et al.2025 · 9 citations
  2. ART: Adaptive Reasoning Trees for Explainable Claim VerificationFindings of the Association for Computational LinguisticsSahil Wadhwa, Himanshu Kumar, Guanqun Yang, et al.2026 · 1 citation
  3. Adaptive Instruction Composition for Automated LLM Red-Teaming ↗Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetJesse Zymet et al.2026

 Co-authors here

1 co-author 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 9 times (of the 149,439 papers whose bibliographies we read); 2 citing papers with a page here →.

Updated

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