1 citations · 1 across the 16 of their papers we have counts for
19 papers
Combinatorics of degeneracy in vertical systems
Carles Checa, Nidhi Kaihnsa
We characterize the generic consistency of vertical systems in terms of the iterated circuits of the column matroid of the coefficient matrix. More precisely, we prove that such a…
ReproAgent: Contract-Guided Paper-to-Code Reproduction
Xue Hu, Zewei Pan, Zhongyuan Wang +3
Paper-to-code reproduction asks scientific AI agents to turn research papers into executable repositories that preserve the paper's method, protocol and artifacts. This is difficul…
SA-Bench: Evaluating Semantic Alignment in LLM-Based Paper Reproduction
Xue Hu, Zewei Pan, Zeli Su +2
LLM agents can generate paper reproduction code, yet often produce scientifically unfaithful implementations. We define this failure mode as semantic drift, where generated code si…
ExRole: From Team Trajectories to Executable Roles in Multi-Agent Language Models
Zhou Liu, Chaoyang Han, Zewei Pan +2
Roles provide an interpretable interface for organizing language-model agents, yet most multi-agent systems treat them as hand-written prompt labels disconnected from learned behav…
SkillLens: Visual Skill Cards for Retrieval-Augmented GUI Action Prediction and On-Policy Distillation
Zhou Liu, Ligang Huang, Zeli Su +5
Computer-using agents can perceive rich software interfaces, yet their decisions often lack visual procedural memory: they may recognize individual controls without identifying whi…
CITBench: A Comprehensive Benchmark for Interactive Tabular Data Processing with LLMs
Zihan Nan, Yang Gu, Wei Liu +4
Tabular data processing is central to data work, and LLM-based assistants have recently shown promising capabilities in supporting such tasks. However, existing benchmarks primaril…
VGGT-Edit: Feed-forward Native 3D Scene Editing with Residual Field Prediction
Kaixin Zhu, Yiwen Tang, Yifan Yang +9
High-quality 3D scene reconstruction has recently advanced toward generalizable feed-forward architectures, enabling the generation of complex environments in a single forward pass…
Reinforcement Learning with Semantic Rewards Enables Low-Resource Language Expansion without Alignment Tax
Zeli Su, Ziyin Zhang, Zhou Liu +7
Extending large language models (LLMs) to low-resource languages often incurs an "alignment tax": improvements in the target language come at the cost of catastrophic forgetting in…
One-Eval: An Agentic System for Automated and Traceable LLM Evaluation
Chengyu Shen, Yanheng Hou, Minghui Pan +8
Reliable evaluation is essential for developing and deploying large language models, yet in practice it often requires substantial manual effort: practitioners must identify approp…
Research on World Models Is Not Merely Injecting World Knowledge into Specific Tasks
Bohan Zeng, Kaixin Zhu, Daili Hua +24
World models have emerged as a critical frontier in AI research, aiming to enhance large models by infusing them with physical dynamics and world knowledge. The core objective is t…
SciFlow-Bench: Evaluating Structure-Aware Scientific Diagram Generation via Inverse Parsing
Tong Zhang, Honglin Lin, Zhou Liu +2
Scientific diagrams convey explicit structural information, yet modern text-to-image models often produce visually plausible but structurally incorrect results. Existing benchmarks…
DataCross: A Unified Benchmark and Agent Framework for Cross-Modal Heterogeneous Data Analysis
Ruyi Qi, Zhou Liu, Wentao Zhang
In real-world data science and enterprise decision-making, critical information is often fragmented across directly queryable structured sources (e.g., SQL, CSV) and "zombie data"…
DataFlow: An LLM-Driven Framework for Unified Data Preparation and Workflow Automation in the Era of Data-Centric AI
Hao Liang, Xiaochen Ma, Zhou Liu +32
The rapidly growing demand for high-quality data in Large Language Models (LLMs) has intensified the need for scalable, reliable, and semantically rich data preparation pipelines.…
DataGovBench: Benchmarking LLM Agents for Real-World Data Governance Workflows
Zhou Liu, Zhaoyang Han, Guochen Yan +5
Data governance ensures data quality, security, and compliance through policies and standards, a critical foundation for scaling modern AI development. Recently, large language mod…
SHRP: Specialized Head Routing and Pruning for Efficient Encoder Compression
Zeli Su, Ziyin Zhang, Wenzheng Zhang +3
Transformer encoders are widely deployed in large-scale web services for natural language understanding tasks such as text classification, semantic retrieval, and content ranking.…
Paper2SysArch: Structure-Constrained System Architecture Generation from Scientific Papers
Ziyi Guo, Zhou Liu, Wentao Zhang
The manual creation of system architecture diagrams for scientific papers is a time-consuming and subjective process, while existing generative models lack the necessary structural…
UniDataBench: Evaluating Data Analytics Agents Across Structured and Unstructured Data
Han Weng, Zhou Liu, Yuanfeng Song +3
In the real business world, data is stored in a variety of sources, including structured relational databases, unstructured databases (e.g., NoSQL databases), or even CSV/excel fil…
LongInsightBench: A Comprehensive Benchmark for Evaluating Omni-Modal Models on Human-Centric Long-Video Understanding
ZhaoYang Han, Qihan Lin, Hao Liang +3
We introduce \textbf{LongInsightBench}, the first benchmark designed to assess models' ability to understand long videos, with a focus on human language, viewpoints, actions, and o…
MAGI: Multi-Agent Guided Interview for Psychiatric Assessment
Guanqun Bi, Zhuang Chen, Zhoufu Liu +9
Automating structured clinical interviews could revolutionize mental healthcare accessibility, yet existing large language models (LLMs) approaches fail to align with psychiatric d…