31 citations · 36 across the 9 of their papers we have counts for
9 papers
CALRK-Bench: Evaluating Context-Aware Legal Reasoning in Korean Law
JiHyeok Jung, TaeYoung Yoon, HyunSouk Cho
Legal reasoning requires not only the application of legal rules but also an understanding of the context in which those rules operate. However, existing legal benchmarks primarily…
Collaborative Learning with Multiple Foundation Models for Source-Free Domain Adaptation
Huisoo Lee, Jisu Han, Hyunsouk Cho +1
Source-Free Domain Adaptation (SFDA) aims to adapt a pre-trained source model to an unlabeled target domain without access to source data. Recent advances in Foundation Models (FMs…
Towards Fully-Automated Materials Discovery via Large-Scale Synthesis Dataset and Expert-Level LLM-as-a-Judge
Heegyu Kim, Taeyang Jeon, Seungtaek Choi +12
Materials synthesis is vital for innovations such as energy storage, catalysis, electronics, and biomedical devices. Yet, the process relies heavily on empirical, trial-and-error m…
DCC: Differentiable Cardinality Constraints for Partial Index Tracking
Wooyeon Jo, Hyunsouk Cho
Index tracking is a popular passive investment strategy aimed at optimizing portfolios, but fully replicating an index can lead to high transaction costs. To address this, partial…
FLEX: Expert-level False-Less EXecution Metric for Reliable Text-to-SQL Benchmark
Heegyu Kim, Taeyang Jeon, Seunghwan Choi +2
Text-to-SQL systems have become crucial for translating natural language into SQL queries in various industries, enabling non-technical users to perform complex data operations. Th…
Multi-intent-aware Session-based Recommendation
Minjin Choi, Hye-young Kim, Hyunsouk Cho +1
Session-based recommendation (SBR) aims to predict the following item a user will interact with during an ongoing session. Most existing SBR models focus on designing sophisticated…
Break the Breakout: Reinventing LM Defense Against Jailbreak Attacks with Self-Refinement
Heegyu Kim, Sehyun Yuk, Hyunsouk Cho
Caution: This paper includes offensive words that could potentially cause unpleasantness. Language models (LMs) are vulnerable to exploitation for adversarial misuse. Training LMs…
Can Large Language Models be Good Emotional Supporter? Mitigating Preference Bias on Emotional Support Conversation
Dongjin Kang, Sunghwan Kim, Taeyoon Kwon +5
Emotional Support Conversation (ESC) is a task aimed at alleviating individuals' emotional distress through daily conversation. Given its inherent complexity and non-intuitive natu…
GTA: Gated Toxicity Avoidance for LM Performance Preservation
Heegyu Kim, Hyunsouk Cho
Caution: This paper includes offensive words that could potentially cause unpleasantness. The fast-paced evolution of generative language models such as GPT-4 has demonstrated outs…