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20222026
most citedIs the Elephant Flying? Resolving Ambiguities in Text-to-Image Generative Models

5 citations · 8 across the 6 of their papers we have counts for

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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.CL20251 cited

LLM-as-a-Judge: Rapid Evaluation of Legal Document Recommendation for Retrieval-Augmented Generation

Anu Pradhan, Alexandra Ortan, Apurv Verma +1

The evaluation bottleneck in recommendation systems has become particularly acute with the rise of Generative AI, where traditional metrics fall short of capturing nuanced quality…

cs.CL2025

Watermarking Degrades Alignment in Language Models: Analysis and Mitigation

Apurv Verma, NhatHai Phan, Shubhendu Trivedi

Watermarking has become a practical tool for tracing language model outputs, but it modifies token probabilities at inference time, which were carefully tuned by alignment training…

cs.CL2024

Operationalizing a Threat Model for Red-Teaming Large Language Models (LLMs)

Apurv Verma, Satyapriya Krishna, Sebastian Gehrmann +7

Creating secure and resilient applications with large language models (LLM) requires anticipating, adjusting to, and countering unforeseen threats. Red-teaming has emerged as a cri…

cs.CL20225 cited

Is the Elephant Flying? Resolving Ambiguities in Text-to-Image Generative Models

Ninareh Mehrabi, Palash Goyal, Apurv Verma +7

Natural language often contains ambiguities that can lead to misinterpretation and miscommunication. While humans can handle ambiguities effectively by asking clarifying questions…

cs.CL20222 cited

Mitigating Gender Bias in Distilled Language Models via Counterfactual Role Reversal

Umang Gupta, Jwala Dhamala, Varun Kumar +7

Language models excel at generating coherent text, and model compression techniques such as knowledge distillation have enabled their use in resource-constrained settings. However,…