1 citations · 1 across the 9 of their papers we have counts for
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SPINE: Measuring LLM Sycophancy under Sustained Multi-Turn Pressure
Leyuan Tang, Kangda Wei, Tianyu Jiang +1
Large language models (LLMs) may abandon correct positions when users push back, exhibiting a failure mode known as sycophancy. Existing evaluations typically use short, prespecifi…
Sycophantic Praise: Evaluating Excessive Praise in Language Models
Daniel Vennemeyer, Phan Anh Duong, Meryl Ye +2
Sycophancy in language models is typically studied as excessive agreement or validation, while explicit praise and flattery have received comparatively little attention. We argue t…
Mitigating Gender Bias via Fostering Exploratory Thinking in LLMs
Kangda Wei, Hasnat Md Abdullah, Ruihong Huang
Large Language Models (LLMs) often exhibit gender bias, resulting in unequal treatment of male and female subjects across different contexts. To address this issue, we propose a no…
CliME: Evaluating Multimodal Climate Discourse on Social Media and the Climate Alignment Quotient (CAQ)
Abhilekh Borah, Hasnat Md Abdullah, Kangda Wei +1
The rise of Large Language Models (LLMs) has raised questions about their ability to understand climate-related contexts. Though climate change dominates social media, analyzing it…
LegalCore: A Dataset for Event Coreference Resolution in Legal Documents
Kangda Wei, Xi Shi, Jonathan Tong +5
Recognizing events and their coreferential mentions in a document is essential for understanding semantic meanings of text. The existing research on event coreference resolution is…
Are LLMs Good Annotators for Discourse-level Event Relation Extraction?
Kangda Wei, Aayush Gautam, Ruihong Huang
Large Language Models (LLMs) have demonstrated proficiency in a wide array of natural language processing tasks. However, its effectiveness over discourse-level event relation extr…