Papers by Soomin Kim
Assessing How Users Display Self-Disclosure and Authenticity in Conversation with Human-Like Agents: A Case Study of Luda Lee (2022.findings-aacl)
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| Challenge: | Existing studies on how people interact with conversational agents have not investigated the interaction authenticity of human-like agents. |
| Approach: | They construct a taxonomy to discern the users’ self-disclosure in the dialogue and the communication authenticity displayed in the user posting. |
| Outcome: | The proposed taxonomy can be used for future research and industrial development. |
HarDBench: A Benchmark for Draft-Based Co-Authoring Jailbreak Attacks for Safe Human–LLM Collaborative Writing (2026.acl-long)
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| Challenge: | Large language models are increasingly used as coauthors in collaborative writing . however, this capability poses a serious safety risk . |
| Approach: | They propose a safety-utility balanced alignment approach to train LLMs to refuse harmful completions while remaining helpful on benign drafts. |
| Outcome: | The proposed method reduces harmful outputs without degrading performance on co-authoring capabilities. |
Feeling Right vs. Being Right: How AI Sycophancy Affects Value-Laden Deliberation (2026.acl-long)
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| Challenge: | Unlike human flattery, AI sycophancy is intentional and self-interested . scophancies are a byproduct of RLHF's user-preference alignment process . |
| Approach: | They propose to operationalize AI sycophancy as excessive face-saving, either active (preserving positive face through agreement) or passive (preserving negative face by withholding challenge). |
| Outcome: | The findings show that sycophancy is a byproduct of RLHF's user-preference alignment process and that it is not a human trait. |