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20232026
most citedAgent Aggregator with Mask Denoise Mechanism for Histopathology Whole Slide Image Analysis

16 citations · 21 across the 28 of their papers we have counts for

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Showing 2026Show all

7 papers · 1 filter

cs.CV2026

Learning latent progression states from spatial heterogeneity in uterine histopathology

Qiming He, Yan Liu, Shuang Ge +20

Tumor progression is accompanied by changes in architecture, morphology and microenvironmental organization, yet progression-associated heterogeneity is usually compressed into sta…

cs.CV2026

DeCo-MIL: Debiased Counterfactual Reasoning for Long-Tailed Whole Slide Image Analysis

Xiaoxiao Li, Xitong Ling, Jiawen Li +6

Multiple instance learning (MIL) is widely used for weakly supervised whole slide image (WSI) analysis. However, under long-tailed distributions, MIL-based WSI analysis faces a nes…

cs.CL2026

ConRub-Med: Reinforcement Learning with Consensus Rubrics for Open-Ended Medical Question Answering

Taojie Zhu, Yuan Xia, Tao Sun +8

Reinforcement learning with verifiable rewards has been especially effective in mathematics and coding, where answers can be checked automatically. Many open-ended medical question…

cs.AI2026

From Knowing to Doing: A Memory-Controlled Benchmark for LLM Trading Agents on Stock Markets

Taojie Zhu, Wentao Zhao, Rui Sun +7

Evaluating whether large language model (LLM) agents can profit in capital markets is increasingly framed as end-to-end trading: place an agent in a historical market, let it trade…

cs.CV2026

Beyond ViT Tokens: Masked-Diffusion Pretrained Convolutional Pathology Foundation Model for Cell-Level Dense Prediction

Weiming Chen, Xitong Ling, Zhenyang Cai +5

Cell-level dense prediction is central to computational pathology, but remains challenging due to fine-grained histological structures, strong domain shifts, and costly dense annot…

cs.LG2026

Bridging SFT and RL: Dynamic Policy Optimization for Robust Reasoning

Taojie Zhu, Dongyang Xu, Ding Zou +4

Post-training paradigms for Large Language Models (LLMs), primarily Supervised Fine-Tuning (SFT) and Reinforcement Learning (RL), face a fundamental dilemma: SFT provides stability…

eess.IV2026

To What Extent Do Token-Level Representations from Pathology Foundation Models Improve Dense Prediction?

Weiming Chen, Xitong Ling, Xidong Wang +10

Pathology foundation models (PFMs) have rapidly advanced and are becoming a common backbone for downstream clinical tasks, offering strong transferability across tissues and instit…