collaborators

12 papers

cs.LG2026

Same Concept, Different Directions: Cross-Modal Feature Heterogeneity in Sparse Autoencoders

Chungpa Lee, Jihoon Kwon, Kyle Min +1

Vision-language models map images and text into a joint embedding space. However, these embeddings often entangle multiple semantic features, which limits their interpretability an…

cs.CL2026

Distributional Alignment as a Criterion for Designing Task Vectors in In-Context Learning

Jihoon Kwon, Jiwon Choi, Jy-yong Sohn

In-context learning (ICL) allows large language models (LLMs) to adapt to new tasks through demonstrations, yet it suffers from escalating inference costs as context length increas…

q-fin.ST2026

Bridging Language Models and Financial Analysis

Alejandro Lopez-Lira, Jihoon Kwon, Sangwoon Yoon +2

The rapid advancements in Large Language Models (LLMs) have unlocked transformative possibilities in natural language processing, particularly within the financial sector. Financia…

cs.CE2026

From Text to Alpha: Can LLMs Track Evolving Signals in Corporate Disclosures?

Chanyeol Choi, Yoon Kim, Yu Yu +10

Natural language processing (NLP) has been widely used in quantitative finance, but traditional methods often struggle to capture rich narratives in corporate disclosures, leaving…

q-fin.GN2026

Forecasting Future Language: Context Design for Mention Markets

Sumin Kim, Jihoon Kwon, Yoon Kim +9

Mention markets, a type of prediction market in which contracts resolve based on whether a specified keyword is mentioned during a future public event, require accurate probabilist…

q-fin.RM2026

LLM as a Risk Manager: LLM Semantic Filtering for Lead-Lag Trading in Prediction Markets

Sumin Kim, Minjae Kim, Jihoon Kwon +7

Prediction markets provide a unique setting where event-level time series are directly tied to natural-language descriptions, yet discovering robust lead-lag relationships remains…