4 citations · 8 across the 16 of their papers we have counts for
17 papers
Uncovering Intervention Opportunities for Suicide Prevention with Language Model Assistants
Jaspreet Ranjit, Hyundong J. Cho, Claire J. Smerdon +5
Warning: This paper discusses topics of suicide and suicidal ideation, which may be distressing to some readers. The National Violent Death Reporting System (NVDRS) documents infor…
Can Vision Language Models Understand Mimed Actions?
Hyundong Cho, Spencer Lin, Tejas Srinivasan +4
Nonverbal communication (NVC) plays an integral role in human language, but studying NVC in general is challenging because of its broad scope and high variance in interpretation am…
Which Questions Improve Learning the Most? Utility Estimation of Questions with LM-based Simulations
Dong-Ho Lee, Hyundong Cho, Jonathan May +1
Asking questions is fundamental for deeper understanding, yet evaluating and generating questions that improve downstream outcomes remains a challenging problem. To address this ga…
Tuning-Free Personalized Alignment via Trial-Error-Explain In-Context Learning
Hyundong Cho, Karishma Sharma, Nicolaas Jedema +4
Language models are aligned to the collective voice of many, resulting in generic outputs that do not align with specific users' styles. In this work, we present Trial-Error-Explai…
NewsEdits 2.0: Learning the Intentions Behind Updating News
Alexander Spangher, Kung-Hsiang Huang, Hyundong Cho +1
As events progress, news articles often update with new information: if we are not cautious, we risk propagating outdated facts. In this work, we hypothesize that linguistic featur…
NewsInterview: a Dataset and a Playground to Evaluate LLMs' Ground Gap via Informational Interviews
Alexander Spangher, Michael Lu, Sriya Jeslyn Kalyan +3
Large Language Models (LLMs) have demonstrated impressive capabilities in generating coherent text but often struggle with grounding language and strategic dialogue. To address thi…
Speechworthy Instruction-tuned Language Models
Hyundong Cho, Nicolaas Jedema, Leonardo F. R. Ribeiro +5
Current instruction-tuned language models are exclusively trained with textual preference data and thus are often not aligned with the unique requirements of other modalities, such…
BotEval: Facilitating Interactive Human Evaluation
Hyundong Cho, Thamme Gowda, Yuyang Huang +3
Following the rapid progress in natural language processing (NLP) models, language models are applied to increasingly more complex interactive tasks such as negotiations and conver…
Aligning Language Models with Demonstrated Feedback
Omar Shaikh, Michelle S. Lam, Joey Hejna +4
Language models are aligned to emulate the collective voice of many, resulting in outputs that align with no one in particular. Steering LLMs away from generic output is possible t…
Can Language Model Moderators Improve the Health of Online Discourse?
Hyundong Cho, Shuai Liu, Taiwei Shi +8
Conversational moderation of online communities is crucial to maintaining civility for a constructive environment, but it is challenging to scale and harmful to moderators. The inc…
RECAP: Retrieval-Enhanced Context-Aware Prefix Encoder for Personalized Dialogue Response Generation
Shuai Liu, Hyundong J. Cho, Marjorie Freedman +2
Endowing chatbots with a consistent persona is essential to an engaging conversation, yet it remains an unresolved challenge. In this work, we propose a new retrieval-enhanced appr…
Continual Dialogue State Tracking via Example-Guided Question Answering
Hyundong Cho, Andrea Madotto, Zhaojiang Lin +5
Dialogue systems are frequently updated to accommodate new services, but naively updating them by continually training with data for new services in diminishing performance on prev…
Analyzing Norm Violations in Live-Stream Chat
Jihyung Moon, Dong-Ho Lee, Hyundong Cho +6
Toxic language, such as hate speech, can deter users from participating in online communities and enjoying popular platforms. Previous approaches to detecting toxic language and no…
Reflect, Not Reflex: Inference-Based Common Ground Improves Dialogue Response Quality
Pei Zhou, Hyundong Cho, Pegah Jandaghi +4
Human communication relies on common ground (CG), the mutual knowledge and beliefs shared by participants, to produce coherent and interesting conversations. In this paper, we demo…
Know Thy Strengths: Comprehensive Dialogue State Tracking Diagnostics
Hyundong Cho, Chinnadhurai Sankar, Christopher Lin +5
Recent works that revealed the vulnerability of dialogue state tracking (DST) models to distributional shifts have made holistic comparisons on robustness and qualitative analyses…
Viola: A Topic Agnostic Generate-and-Rank Dialogue System
Hyundong Cho, Basel Shbita, Kartik Shenoy +5
We present Viola, an open-domain dialogue system for spoken conversation that uses a topic-agnostic dialogue manager based on a simple generate-and-rank approach. Leveraging recent…
Grounding Conversations with Improvised Dialogues
Hyundong Cho, Jonathan May
Effective dialogue involves grounding, the process of establishing mutual knowledge that is essential for communication between people. Modern dialogue systems are not explicitly t…