Papers by Ashiqur R. KhudaBukhsh
Hope vs. Hate: Understanding User Interactions with LGBTQ+ News Content in Mainstream US News Media through the Lens of Hope Speech (2025.emnlp-main)
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| Challenge: | a new study examines how users interact with LGBTQ+ news content . a corpus of 1,419,047 comments on 3,161 YouTube news videos is used to analyze the content - both positive and negative - of cable news outlets. |
| Approach: | They analyze how users interact with LGBTQ+ news content via a corpus of 1,419,047 comments on 3,161 YouTube news videos of major US cable news outlets. |
| Outcome: | The proposed classifier detects positive (hope speech), negative, neutral, and irrelevant content. |
What About the Scene With the Hitler Reference? HAUNT: A Framework to Probe LLMs’ Self-consistency in Closed Domains Via Adversarial Nudge (2026.acl-long)
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| Challenge: | Claude exhibits strong resilience, while GPT and Grok demonstrate moderate resilience . open models fall short significantly, while proprietary models exhibit weak resilience compared to open models . |
| Approach: | They propose a framework for stress testing factual fidelity in large language models in the presence of adversarial nudges. |
| Outcome: | The proposed model is robust to adversarial nudges in two closed domains. |
Auditing LLM Responses to Harmful Stereotypes Targeting Mental Health Groups (2026.findings-acl)
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| Challenge: | Large Language Models (LLMs) can exhibit imbalanced biases against vulnerable groups, but how they rationalize stereotypes and rights restrictions targeting mental health entities remains underexplored. |
| Approach: | They audit a suite of open-weight LLMs on stereotype-justification prompts tied to mental health identities. |
| Outcome: | The proposed models endorse harmful stereotypes when explicitly asked to justify them, with endorsement varying across model families, versions, and mental health conditions. |