works on

From the 1 of 9 linked papers with an AI index.

activity
20242026
collaborators

9 papers

cs.CL2026

Can Induced Emotion Bias LLM Behaviors in Sequential Decision Making?

Minh Khoi Ho, Zihao Zhu, Runchuan Zhu +4

The paper studies whether artificially induced emotions affect the decision-making of large language model agents in the Iowa Gambling Task, finding that overall emotions do not bi…

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…

cs.CL2026

No Hidden Prompts Needed! You Can Game AI Peer Review with Presentation-Only Revisions

Xu Yang, Zhizhou Sha, Junbo Li +10

As AI-generated reviews move from experimental tools into peer-review infrastructure, most robustness concerns have focused on explicit attacks such as hidden instructions and prom…

cs.CL2026

LLMs Can Get "Brain Rot": A Pilot Study on Twitter/X

Shuo Xing, Junyuan Hong, Yifan Wang +5

We propose and test the LLM Brain Rot Hypothesis: continual exposure to junk web text induces lasting cognitive decline in large language models (LLMs). To unveil junk effects, we…

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…