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Chirag Agarwal

University of Virginia

37 papers hereh-index 242.4k citations62 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author10
  • middle author19
  • last author5

Across the 34 of 37 papers where every author was matched, so the position is known.

fields
  • cs.LG13
  • cs.CL8
  • cs.CV7
  • cs.AI3
  • cs.CR2
  • cs.MM2
affiliations
  • University of Virginia
Homepage
same name
  • Chirag Agarwal — 9 papers, h 3
  • Chirag Agarwal — 6 papers, h 2
  • Chirag Agarwal — 6 papers, h 3
  • Chirag Agarwal — 2 papers, h 1
  • Chirag Agarwal — 1 paper, h 0
  • Chirag Agarwal — 1 paper, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20172026
most citedOpenXAI: Towards a Transparent Evaluation of Model Explanations

82 citations · 264 across the 36 of their papers we have counts for

collaborators
Showing 2023 · cs.CLShow all

3 papers · 2 filters

cs.CL2023★ 1 cited

Quantifying Uncertainty in Natural Language Explanations of Large Language Models

Sree Harsha Tanneru, Chirag Agarwal, Himabindu Lakkaraju

Large Language Models (LLMs) are increasingly used as powerful tools for several high-stakes natural language processing (NLP) applications. Recent prompting works claim to elicit…

cs.CL2023★ 7 cited

In-Context Explainers: Harnessing LLMs for Explaining Black Box Models

Nicholas Kroeger, Dan Ley, Satyapriya Krishna +2

Recent advancements in Large Language Models (LLMs) have demonstrated exceptional capabilities in complex tasks like machine translation, commonsense reasoning, and language unders…

cs.CL2023★ 25 cited

Certifying LLM Safety against Adversarial Prompting

Aounon Kumar, Chirag Agarwal, Suraj Srinivas +3

Large language models (LLMs) are vulnerable to adversarial attacks that add malicious tokens to an input prompt to bypass the safety guardrails of an LLM and cause it to produce ha…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.