13 citations · 44 across the 37 of their papers we have counts for
15 papers · 1 filter
Natural-Language Policies to Executable Decisions: An Interpretable Large Language Model Framework
Ziqiang Zhang, Jing Ma, Zilong Wang +6
Pricing automation in large-scale tourism is challenging because travel orders are highly unstructured, while pricing policies are complex, rapidly evolving, and inherently open-en…
A report-grounded vision-language foundation model for colonoscopy from 280000 routine reports
Jia Yu, Yan Zhu, Yili He +12
Vision-language models remain underused in colonoscopy despite the rich expert descriptions recorded in routine reports. These reports document lesion appearance, size and location…
Dementia Etiology Diagnosis via Collaborative Meta Knowledge Enhancement
Siyuan Du, Mengxi Chen, Xinyang Jiang +6
Although artificial intelligence (AI) has shown promising performance in several medical tasks, accurate dementia etiology diagnosis with AI remains challenging due to complex over…
Dual-Branch Cross-Projection Debiasing through Diffusion-based Disentanglement
Xiangqian Zhao, Xinyang Jiang, Zhipeng Xu +5
Foundation models trained on biased datasets often rely on spurious correlations between target labels and non-causal attributes, resulting in poor generalization on minority group…
Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale
Ang Li, Ben Liu, Bin Han +215
Efficient and scalable agentic intelligence requires models that can deliver both low-latency responses and strong reasoning capabilities while remaining practical to train, serve,…
MedCUA-Bench: A Screenshot-Only Benchmark for Clinical Computer-Use Agents
Jia Yu, Zilong Wang, Xinyang Jiang +2
Computer-use agents could automate repetitive screen-based clinical work, but their reliability in medical graphical user interfaces remains largely unvalidated. Existing benchmark…
CogRAG: Tackling Heterogeneous Cognitive Demands in RAG via Stratified Retrieval and Reasoning
Xudong Wang, Zilong Wang, Kui Su +1
Retrieval-Augmented Generation (RAG) frameworks typically process all queries through a one-size-fits-all pipeline, ignoring the heterogeneous cognitive demands of different tasks.…
From Static Inference to Dynamic Interaction: A Survey of Streaming Large Language Models
Junlong Tong, Zilong Wang, YuJie Ren +4
Standard Large Language Models (LLMs) are predominantly designed for static inference with pre-defined inputs, which limits their applicability in dynamic, real-time scenarios. To…
CocoaBench: Evaluating Unified Digital Agents in the Wild
CocoaBench Team, Shibo Hao, Zhining Zhang +29
LLM agents now perform strongly in software engineering, deep research, GUI automation, and various other applications, while recent agent scaffolds and models are increasingly int…
Reasoning-Driven Multimodal LLM for Domain Generalization
Zhipeng Xu, Zilong Wang, Xinyang Jiang +3
This paper addresses the domain generalization (DG) problem in deep learning. While most DG methods focus on enforcing visual feature invariance, we leverage the reasoning capabili…
OMGs: A multi-agent system supporting MDT decision-making across the ovarian tumour care continuum
Yangyang Zhang, Zilong Wang, Jianbo Xu +24
Ovarian tumour management has increasingly relied on multidisciplinary tumour board (MDT) deliberation to address treatment complexity and disease heterogeneity. However, most pati…
Mirror: A Multi-Agent System for AI-Assisted Ethics Review
Yifan Ding, Yuhui Shi, Zhiyan Li +10
Ethics review is a foundational mechanism of modern research governance, yet contemporary systems face increasing strain as ethical risks arise as structural consequences of large-…
Terminal-Bench: Benchmarking Agents on Hard, Realistic Tasks in Command Line Interfaces
Mike A. Merrill, Alexander G. Shaw, Nicholas Carlini +82
AI agents may soon become capable of autonomously completing valuable, long-horizon tasks in diverse domains. Current benchmarks either do not measure real-world tasks, or are not…
A Safety Report on GPT-5.2, Gemini 3 Pro, Qwen3-VL, Grok 4.1 Fast, Nano Banana Pro, and Seedream 4.5
Xingjun Ma, Yixu Wang, Hengyuan Xu +18
The rapid evolution of Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs) has driven major gains in reasoning, perception, and generation across language and…
GI-Bench: A Panoramic Benchmark Revealing the Knowledge-Experience Dissociation of Multimodal Large Language Models in Gastrointestinal Endoscopy Against Clinical Standards
Yan Zhu, Te Luo, Pei-Yao Fu +12
Multimodal Large Language Models (MLLMs) show promise in gastroenterology, yet their performance against comprehensive clinical workflows and human benchmarks remains unverified. T…