1 citations · 3 across the 19 of their papers we have counts for
19 papers
PinSieve: Production Selective VLM Serving and a Governed Memory Flywheel for Enterprise Content-Quality Triage
Chuqing Gao, Yuanfang Song, Jonathan Zhang +4
Enterprise AI agents in production often need to be bounded, stateful, observable, and governable rather than fully autonomous. We present PinSieve, a production case study in a la…
UI2App: Benchmarking Visual Interaction Inference in Executable Web Application Generation
Grace Man Chen, Litao Guo, Yifan Wu +5
Large language models (LLMs) have demonstrated growing competence in generating web pages from UI screenshots, which convey both visual structure and cues to application behavior.…
Foundation Protocol: A Coordination Layer for Agentic Society
Bang Liu, Yongfeng Gu, Jiayi Zhang +26
Autonomous agents are moving from tools into a layer of social infrastructure: they browse, purchase, deploy software, manage systems, and increasingly interact with one another. A…
DiagEval: Trajectory-Conditioned Diagnosis for Reliable Software Evaluation with GUI Agents
Sirui Hong, Zhijie Liu, Tengfei Li +3
Evaluating LLM-generated interactive software requires execution in addition to static analysis. The key difficulty is that correctness is a graph-level reachable property over lat…
AutoWebWorld: Synthesizing Infinite Verifiable Web Environments via Finite State Machines
Yifan Wu, Yiran Peng, Yiyu Chen +12
The performance of autonomous Web GUI agents heavily relies on the quality and quantity of their training data. However, a fundamental bottleneck persists: collecting interaction t…
OmniMoE: An Efficient MoE by Orchestrating Atomic Experts at Scale
Jingze Shi, Zhangyang Peng, Yizhang Zhu +3
Mixture-of-Experts (MoE) architectures are evolving towards finer granularity to improve parameter efficiency. However, existing MoE designs face an inherent trade-off between the…
AutoEnv: Automated Environments for Measuring Cross-Environment Agent Learning
Jiayi Zhang, Yiran Peng, Fanqi Kong +12
Humans naturally adapt to diverse environments by learning underlying rules across worlds with different dynamics, observations, and reward structures. In contrast, existing agents…
InteractComp: Evaluating Search Agents With Ambiguous Queries
Mingyi Deng, Lijun Huang, Yani Fan +23
Language agents have demonstrated remarkable potential in web search and information retrieval. However, many search-agent benchmarks assume that user queries are complete and unam…
ReCode: Unify Plan and Action for Universal Granularity Control
Zhaoyang Yu, Jiayi Zhang, Huixue Su +9
Real-world tasks require decisions at varying granularities, and humans excel at this by leveraging a unified cognitive representation where planning is fundamentally understood as…
VisJudge-Bench: Aesthetics and Quality Assessment of Visualizations
Yupeng Xie, Zhiyang Zhang, Yifan Wu +8
Visualization, a domain-specific yet widely used form of imagery, is an effective way to turn complex datasets into intuitive insights, and its value depends on whether data are fa…
Beyond Structure: Invariant Crystal Property Prediction with Pseudo-Particle Ray Diffraction
Bin Cao, Yang Liu, Longhan Zhang +6
Crystal property prediction, governed by quantum mechanical principles, is computationally prohibitive to solve exactly for large many-body systems using traditional density functi…
Trainable Dynamic Mask Sparse Attention
Jingze Shi, Yifan Wu, Yiran Peng +4
The increasing demand for long-context modeling in large language models (LLMs) is bottlenecked by the quadratic complexity of the standard self-attention mechanism. The community…
ChartMark: A Structured Grammar for Chart Annotation
Yiyu Chen, Yifan Wu, Shuyu Shen +4
Chart annotations enhance visualization accessibility but suffer from fragmented, non-standardized representations that limit cross-platform reuse. We propose ChartMark, a structur…
TransXSSM: A Hybrid Transformer State Space Model with Unified Rotary Position Embedding
Bingheng Wu, Jingze Shi, Yifan Wu +2
Transformers exhibit proficiency in capturing long-range dependencies, whereas State Space Models (SSMs) facilitate linear-time sequence modeling. Notwithstanding their synergistic…
Concise Reasoning, Big Gains: Pruning Long Reasoning Trace with Difficulty-Aware Prompting
Yifan Wu, Jingze Shi, Bingheng Wu +4
Existing chain-of-thought (CoT) distillation methods can effectively transfer reasoning abilities to base models but suffer from two major limitations: excessive verbosity of reaso…
ChartCards: A Chart-Metadata Generation Framework for Multi-Task Chart Understanding
Yifan Wu, Lutao Yan, Leixian Shen +3
The emergence of Multi-modal Large Language Models (MLLMs) presents new opportunities for chart understanding. However, due to the fine-grained nature of these tasks, applying MLLM…
Boosting Text-to-Chart Retrieval through Training with Synthesized Semantic Insights
Yifan Wu, Lutao Yan, Yizhang Zhu +6
Text-to-chart retrieval, enabling users to find relevant charts via natural language queries, has gained significant attention. However, evaluating models in real-world business in…
AskChart: Universal Chart Understanding through Textual Enhancement
Xudong Yang, Yifan Wu, Yizhang Zhu +2
Chart understanding tasks such as ChartQA and Chart-to-Text involve automatically extracting and interpreting key information from charts, enabling users to query or convert visual…
ChartInsights: Evaluating Multimodal Large Language Models for Low-Level Chart Question Answering
Yifan Wu, Lutao Yan, Leixian Shen +3
Chart question answering (ChartQA) tasks play a critical role in interpreting and extracting insights from visualization charts. While recent advancements in multimodal large langu…