Papers by Jingwen Cheng
REALM: A Dataset of Real-World LLM Use Cases (2025.findings-acl)
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| Challenge: | Existing studies on LLM adoption and their social implications lack empirical grounding, weakening their validity. |
| Approach: | They propose to integrate a dataset of over 94,000 LLM use cases collected from Reddit and news articles to provide insights into LLM adoption across different domains. |
| Outcome: | The proposed dataset includes over 94,000 LLM use cases collected from Reddit and news articles. |
Chain-of-Thought Prompting Obscures Hallucination Cues in Large Language Models: An Empirical Evaluation (2025.findings-emnlp)
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| Challenge: | Chain-of-Thought (CoT) prompting can mitigate hallucinations by encouraging step-by-step reasoning, but its impact on halluciation detection remains underexplored. |
| Approach: | They conduct an empirical evaluation of CoT prompting in Large Language Models (LLMs) to examine their impact on hallucination detection methods. |
| Outcome: | The proposed method significantly affects the internal states and token probability distributions of the LLM. |