2 citations · 2 across the 12 of their papers we have counts for
12 papers
Behavior-Aware Item Modeling via Dynamic Procedural Solution Representations for Knowledge Tracing
Jun Seo, Sangwon Ryu, Heejin Do +2
Knowledge Tracing (KT) aims to predict learners' future performance from past interactions. While recent KT approaches have improved via learning item representations aligned with…
Leveraging What's Overfixed: Post-Correction via LLM Grammatical Error Overcorrection
Taehee Park, Heejin Do, Gary Geunbae Lee
Robust supervised fine-tuned small Language Models (sLMs) often show high reliability but tend to undercorrect. They achieve high precision at the cost of low recall. Conversely, L…
Adaptive Planning for Multi-Attribute Controllable Summarization with Monte Carlo Tree Search
Sangwon Ryu, Heejin Do, Yunsu Kim +2
Controllable summarization moves beyond generic outputs toward human-aligned summaries guided by specified attributes. In practice, the interdependence among attributes makes it ch…
GuRE:Generative Query REwriter for Legal Passage Retrieval
Daehee Kim, Deokhyung Kang, Jonghwi Kim +2
Legal Passage Retrieval (LPR) systems are crucial as they help practitioners save time when drafting legal arguments. However, it remains an underexplored avenue. One primary reaso…
Revisiting Early Detection of Sexual Predators via Turn-level Optimization
Jinmyeong An, Sangwon Ryu, Heejin Do +3
Online grooming is a severe social threat where sexual predators gradually entrap child victims with subtle and gradual manipulation. Therefore, timely intervention for online groo…
Teach-to-Reason with Scoring: Self-Explainable Rationale-Driven Multi-Trait Essay Scoring
Heejin Do, Sangwon Ryu, Gary Geunbae Lee
Multi-trait automated essay scoring (AES) systems provide a fine-grained evaluation of an essay's diverse aspects. While they excel in scoring, prior systems fail to explain why sp…
Towards Prompt Generalization: Grammar-aware Cross-Prompt Automated Essay Scoring
Heejin Do, Taehee Park, Sangwon Ryu +1
In automated essay scoring (AES), recent efforts have shifted toward cross-prompt settings that score essays on unseen prompts for practical applicability. However, prior methods t…
Multimodal Cognitive Reframing Therapy via Multi-hop Psychotherapeutic Reasoning
Subin Kim, Hoonrae Kim, Heejin Do +1
Previous research has revealed the potential of large language models (LLMs) to support cognitive reframing therapy; however, their focus was primarily on text-based methods, often…
Multi-Facet Blending for Faceted Query-by-Example Retrieval
Heejin Do, Sangwon Ryu, Jonghwi Kim +1
With the growing demand to fit fine-grained user intents, faceted query-by-example (QBE), which retrieves similar documents conditioned on specific facets, has gained recent attent…
Multi-aspect Depression Severity Assessment via Inductive Dialogue System
Chaebin Lee, Seungyeon Seo, Heejin Do +1
With the advancement of chatbots and the growing demand for automatic depression detection, identifying depression in patient conversations has gained more attention. However, prio…
Autoregressive Multi-trait Essay Scoring via Reinforcement Learning with Scoring-aware Multiple Rewards
Heejin Do, Sangwon Ryu, Gary Geunbae Lee
Recent advances in automated essay scoring (AES) have shifted towards evaluating multiple traits to provide enriched feedback. Like typical AES systems, multi-trait AES employs the…
DiagESC: Dialogue Synthesis for Integrating Depression Diagnosis into Emotional Support Conversation
Seungyeon Seo, Gary Geunbae Lee
Dialogue systems for mental health care aim to provide appropriate support to individuals experiencing mental distress. While extensive research has been conducted to deliver adequ…