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20232026
most citedOphtha-LLaMA2: A Large Language Model for Ophthalmology

7 citations · 17 across the 9 of their papers we have counts for

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Showing 2026Show all

6 papers · 1 filter

cs.LG2026

Right Direction, Wrong Step: Geometric Analysis of Finite-Step Failure in Looped Transformers

Zhihao Guo, Zonghan Wu, Haizhou Du +4

Looped Transformers offer a parameter-efficient route to test-time scaling by reusing shared layers for iterative latent reasoning. However, additional iterations can reduce suppor…

cs.CL2026

Mint-Agent: Introducing Finance-Native Agentic Foundation Models

Agent Team, Kun Wang, Gavin Zhang +7

Financial agents must do more than recall domain knowledge: they must be both reliable, executing precise operations over grounded evidence, and executive, sustaining long-horizon…

cs.CL2026

HalluTracer: Pre-Decoding Truthfulness Prediction via Depth-Averaged Probe-Logit

Zhihao Guo, Zonghan Wu, Huan Huo +6

Internal-state probes enable truthfulness prediction before a large language model generates an answer. When detectors change both the layers they read and the rules used to combin…

cs.CL2026

TimeSage-MT: A Multi-Turn Benchmark for Evaluating Agentic Time Series Reasoning

Yaxuan Kong, Qingren Yao, Yuqi Nie +7

Time series data inform critical decisions across many real-world domains. While large language model (LLM) agents can analyze data through natural language and tools, it remains u…

cs.CL2026

SkillBrew: Multi-Objective Curation of Skill Banks for LLM Agents

Wentao Hu, Zhendong Chu, Yiming Zhang +6

Retrieval-augmented LLM agents increasingly rely on curated skill banks: collections of reusable textual principles that guide decision making on complex tasks. Existing approaches…

cs.CV2026

MIRL: Mutual Information-Guided Reinforcement Learning for Vision-Language Models

Yin Zhang, Jiaxuan Zhao, Zonghan Wu +5

Vision-Language Models (VLMs) frequently suffer from visual perception errors and hallucinations that compromise answer accuracy in complex reasoning tasks. Reinforcement Learning…