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20242026
most citedAutomate Strategy Finding with LLM in Quant Investment

3 citations · 9 across the 35 of their papers we have counts for

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Showing 2026 · cs.AIShow all

7 papers · 2 filters

cs.AI2026

Same Probabilities, Different Advice: Gain-Loss Framing Effects in High-Stakes LLM Decision Support

Yuyao Zhang, Yakun Cui, Han Zhu +3

Large language models (LLMs) are increasingly used to support consequential decisions, yet their reliability under equivalent representations of uncertainty remains unclear. Existi…

cs.AI2026

Entertain, then Cancel: How Thinking Makes Reasoning Models Read Some and Or Literally

Zhizhuo Kou, Jian Yang, Pengfei Hao +4

When a speaker says ``some students passed'', listeners infer that not all of them did. Reasoning models now let users decide how long a model thinks before it answers, but we do n…

cs.AI2026

EvoQuantLab: Training-Free Dual-Loop Evolution for Auditable Quantitative Research

Haolin Yang, Zhiqiang Qian, Chutian Chen +7

Automated alpha factor discovery is critical for modern quantitative research. While large language models (LLMs) have increasingly been integrated into quantitative workflows, exi…

cs.AI2026

LexAgentHallu: A Hierarchical Benchmark for Profiling Hallucinations in Legal Agents

Yujin Zhou, Mingxuan Zheng, Chuxue Cao +4

As large language models are increasingly deployed as tool-augmented legal agents, they introduce agentic hallucinations where tool-call and reasoning errors cascade into fabricate…

cs.AI2026

SkillProx: Self-Evolving Agent Skills via Proximal Textual Gradient Descent

Mingxuan Zheng, Yujin Zhou, Chuxue Cao +6

LLM agents increasingly adapt to recurring tasks by accumulating procedural knowledge in skills. These skills are lightweight, reusable textual artifacts that are loaded into the a…

cs.AI2026

LRAS: Advanced Legal Reasoning with Agentic Search

Yujin Zhou, Chuxue Cao, Jinluan Yang +4

While Large Reasoning Models (LRMs) have demonstrated exceptional logical capabilities in mathematical domains, their application to the legal field remains hindered by the strict…

cs.AI2026

Reinforcement Learning of Large Language Models for Interpretable Credit Card Fraud Detection

Cooper Lin, Yanting Zhang, Maohao Ran +7

E-commerce platforms and payment solution providers face increasingly sophisticated fraud schemes, ranging from identity theft and account takeovers to complex money laundering ope…