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Rahul Gupta

11 papers hereh-index 101.1k citations29 works total

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

author position
  • first author1
  • middle author8
  • last author1

Across the 10 of 11 papers where every author was matched, so the position is known.

fields
  • cs.AI6
  • cs.CL4
  • cs.LG1
same name
  • Rahul Gupta — 13 papers, h 5
  • Rahul Gupta — 9 papers, h 4
  • Rahul Gupta — 4 papers, h 5
  • Rahul Gupta — 4 papers, h 2
  • Rahul Gupta — 4 papers, h 53
  • Rahul Gupta — 4 papers, 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
20242026
collaborators
Showing cs.CLShow all

4 papers · 1 filter

cs.CL2026

From Interpretability to Control: Insights from Six Years of the TrustNLP Workshop

Rahul Gupta, Abhinav Mohanty, Anaelia Ovalle +10

The Workshop on Trustworthy Natural Language Processing (TrustNLP), co-located with major ACL conferences since 2021, has grown from 8 proceedings papers to 41 over six editions, d…

cs.CL2026

SWAN: Semantic Watermarking with Abstract Meaning Representation

Ziping Ye, Gourab Dey, Christos Christodoulopoulos +7

We introduce SWAN (Semantic Watermarking with Abstract Meaning Representation), a novel framework that embeds watermark signatures into the semantic structure of a sentence using A…

cs.CL2024

Attribute Controlled Fine-tuning for Large Language Models: A Case Study on Detoxification

Tao Meng, Ninareh Mehrabi, Palash Goyal +6

We propose a constraint learning schema for fine-tuning Large Language Models (LLMs) with attribute control. Given a training corpus and control criteria formulated as a sequence-l…

cs.CL2024

Data Advisor: Dynamic Data Curation for Safety Alignment of Large Language Models

Fei Wang, Ninareh Mehrabi, Palash Goyal +3

Data is a crucial element in large language model (LLM) alignment. Recent studies have explored using LLMs for efficient data collection. However, LLM-generated data often suffers…

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