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20182026
most citedEnhancing Exchange Rate Forecasting with Explainable Deep Learning Models

2 citations · 2 across the 16 of their papers we have counts for

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7 papers · 1 filter

cs.AI2026

What Does Multi-Harness RL Learn? Credit Assignment and Portability in Coding Agents

Chenqian Le, Jiayi Cheng, Qijia He +3

Agent reinforcement learning (RL) increasingly runs through full execution harnesses, and a multi-harness recipe mixes two choices: exposing the policy to several harnesses, and co…

cs.AI2026

CodeRescue: Budget-Calibrated Recovery Routing for Coding Agents

Qijia He, Jiayi Cheng, Chenqian Le +8

Coding agents increasingly operate in executable environments where a failed attempt produces actionable feedback rather than merely an incorrect answer. Existing cost-aware system…

cs.AI2026

PreDiff-LM: Pretrained Discrete Masked Diffusion Language Modeling with Hybrid Attention

Zhengtao Yao, Runhao Li, Xupeng Chen +12

Discrete masked diffusion language models support bidirectional generation and infilling, but adapting pretrained autoregressive (AR) transformers requires reconciling causal pretr…

cs.AI2026

Less Data, Better Alignment: Data-Centric Multi-Evaluator Agreement for Preference Optimization

Zhengtao Yao, Runhao Li, Xupeng Chen +12

Research on preference optimization often varies the training objective while holding the data fixed. We instead ask whether a small, high-confidence set of on-policy responses can…

cs.AI2026

Iterative Multimodal Retrieval-Augmented Generation for Medical Question Answering

Xupeng Chen, Binbin Shi, Chenqian Le +5

Medical retrieval-augmented generation (RAG) systems typically operate on text chunks extracted from biomedical literature, discarding the rich visual content (tables, figures, str…

cs.AI2026

Why Does Grounding Hurt Medical VQA? Benchmarking, Diagnosis, and Fine-Tuning of Vision-Language Models

Xupeng Chen, Binbin Shi, Chenqian Le +5

Vision-language models (VLMs) are increasingly applied to medical visual question answering (Med-VQA), yet whether they can \emph{localize} the evidence behind their answers---a pr…