59 citations · 99 across the 11 of their papers we have counts for
11 papers
TACG: Trajectory-Aware Commit Gating for Diffusion Language Model Decoding
Chengcheng Wang, Tingzhang Luo, Wenhao Li +2
Diffusion language models (DLLMs) generate text by iteratively denoising masked positions, exposing a trajectory of predictive distributions rather than a single instantaneous beli…
From Question Answering to Task Completion: A Survey on Agent System and Harness Design
Jianyuan Guo, Zhiwei Hao, Chengcheng Wang +14
LLM-based agents mark a shift from passive question answering to active task completion: they perceive environments, invoke tools, maintain state, and act over extended horizons. A…
Retrieval-Augmented Linguistic Calibration
Yi-Fan Yeh, Linwei Tao, Minjing Dong +4
Linguistic cues such as "I believe" and "probably" offer an intuitive interface for communicating confidence, yet a generalisable, principled calibration framework for linguistic c…
Adversarial Error Correction for Visual Autoregressive Generation
Ligong Bi, Tao Huang, Jianyuan Guo +1
Visual Autoregressive (VAR) models have emerged as a powerful paradigm for image synthesis by performing hierarchical next-scale prediction. However, VAR models are inherently pron…
Sibyl-AutoResearch: Autonomous Research Needs Self-Evolving Trial-and-Error Harnesses, Not Paper Generators
Chengcheng Wang, Qinhua Xie, Wei He +3
Autonomous research systems increasingly make the scientific workflow executable: agents can propose ideas, run code, inspect results, and draft papers. But executable workflows do…
Circle-RoPE: Cone-like Decoupled Rotary Positional Embedding for Large Vision-Language Models
Chengcheng Wang, Jianyuan Guo, Hongguang Li +4
Rotary Position Embedding (RoPE) is widely adopted in large language models, but when applied to vision-language models (VLMs) it couples text and image position indices and can in…
GeminiFusion: Efficient Pixel-wise Multimodal Fusion for Vision Transformer
Ding Jia, Jianyuan Guo, Kai Han +4
Cross-modal transformers have demonstrated superiority in various vision tasks by effectively integrating different modalities. This paper first critiques prior token exchange meth…
Data-efficient Large Vision Models through Sequential Autoregression
Jianyuan Guo, Zhiwei Hao, Chengcheng Wang +5
Training general-purpose vision models on purely sequential visual data, eschewing linguistic inputs, has heralded a new frontier in visual understanding. These models are intended…
Vision Superalignment: Weak-to-Strong Generalization for Vision Foundation Models
Jianyuan Guo, Hanting Chen, Chengcheng Wang +3
Recent advancements in large language models have sparked interest in their extraordinary and near-superhuman capabilities, leading researchers to explore methods for evaluating an…
One-for-All: Bridge the Gap Between Heterogeneous Architectures in Knowledge Distillation
Zhiwei Hao, Jianyuan Guo, Kai Han +4
Knowledge distillation~(KD) has proven to be a highly effective approach for enhancing model performance through a teacher-student training scheme. However, most existing distillat…
CMT: Convolutional Neural Networks Meet Vision Transformers
Jianyuan Guo, Kai Han, Han Wu +4
Vision transformers have been successfully applied to image recognition tasks due to their ability to capture long-range dependencies within an image. However, there are still gaps…