activity
20242026
collaborators

14 papers

cs.AI2026

When Summaries Distort Decisions: Information Fidelity in LLM-Compressed Financial Analysis

Hoyoung Lee, Suhwan Park, Seunghan Lee +15

Financial decision-makers face more information than they can directly inspect, making context compression necessary. Yet when large language models (LLMs) compress financial sourc…

cs.CL2026

Fund2Persona: A Framework for Building and Refining Financial Advisor Personas from Fund Disclosure Data

Suhwan Park, Hoyoung Lee, Zhangyang Wang +5

Demand for personalized financial advising is growing, but consistent advisor expertise is difficult to obtain, scale, and encode in LLM systems. Simple persona prompts rarely spec…

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…