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20242026
most citedLinq-Embed-Mistral Technical Report

3 citations · 8 across the 18 of their papers we have counts for

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Showing 2026Show all

9 papers · 1 filter

cs.AI2026

FinAutoRubric: Expert-Guided Automatic Rubric Generation for Evaluating Financial Research Agents

Hoyoung Lee, Suyeol Yun, Jack Haverty +17

Evaluating finance research agents requires rubrics that reflect expert standards and fix the values correct as of an information cutoff. Expert-reviewed finance benchmarks rely on…

cs.AI2026

Poisoning Agentic Alpha: Adversarial Vulnerabilities Across Roles and Architectures in Multi-Agent Trading Systems

CheolWon Na, Hao Ni, Lukasz Szpruch +7

LLM-based multi-agent trading systems, in which specialized agents collaborate through structured communication to produce trading decisions, are moving rapidly from research proto…

cs.AI2026

Your AI, On a Dial: Controlling Investment Bias in LLMs with a Single Neuron

Sahong Park, Suhwan Park, Hoyoung Lee +8

Large language models (LLMs) are increasingly used in investment decision-making, yet prior work shows that they exhibit systematic, model-specific investment preferences. We study…

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 advice is growing, yet current LLM-based advisors often fail to provide consistent and specialized guidance. Simple persona prompts rarely specify…

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…

cs.LG2026★ 1 cited

Evaluating LLMs in Finance Requires Explicit Bias Consideration

Yaxuan Kong, Hoyoung Lee, Yoontae Hwang +7

Large Language Models (LLMs) are increasingly integrated into financial workflows, but evaluation practice has not kept up. Finance-specific biases can inflate performance, contami…

cs.CE2026

Cross-Sectional Asset Retrieval via Future-Aligned Soft Contrastive Learning

Hyeongmin Lee, Chanyeol Choi, Jihoon Kwon +8

Asset retrieval (finding similar assets in a financial universe) is central to quantitative investment decision-making. Existing approaches define similarity through historical pri…