1 citations · 3 across the 8 of their papers we have counts for
8 papers
The Blending Ratio Is Not Where the Performance Is: Diagnosing Prototype Blending for Few-Shot Adaptation of Vision-Language Models
Liangzhi Li, Bowen Wang, Yiming Qian +3
Many few-shot adaptation methods for vision-language models classify with a convex combination of the zero-shot text prototype and the mean of the K labelled image features, with a…
CUA-Gym: Scaling Verifiable Training Environments and Tasks for Computer-Use Agents
Bowen Wang, Dunjie Lu, Junli Wang +11
Reinforcement learning with verifiable rewards (RLVR) has driven breakthroughs in domains such as math, tool-use, and software engineering, yet its extension to computer-use agents…
Online Conformal Prediction with Corrupted Feedback
Bowen Wang, Matteo Zecchin, Osvaldo Simeone
Modern artificial intelligence systems require calibrated uncertainty estimates that remain reliable in sequential and non-stationary environments. Online conformal prediction (OCP…
Exploring Visual Prompting: Robustness Inheritance and Beyond
Qi Li, Liangzhi Li, Zhouqiang Jiang +2
Visual Prompting (VP), an efficient method for transfer learning, has shown its potential in vision tasks. However, previous works focus exclusively on VP from standard source mode…
Concatenated Masked Autoencoders as Spatial-Temporal Learner
Zhouqiang Jiang, Bowen Wang, Tong Xiang +4
Learning representations from videos requires understanding continuous motion and visual correspondences between frames. In this paper, we introduce the Concatenated Masked Autoenc…
Towards Robust and Accurate Visual Prompting
Qi Li, Liangzhi Li, Zhouqiang Jiang +1
Visual prompting, an efficient method for transfer learning, has shown its potential in vision tasks. However, previous works focus exclusively on VP from standard source models, i…
MPrompt: Exploring Multi-level Prompt Tuning for Machine Reading Comprehension
Guoxin Chen, Yiming Qian, Bowen Wang +1
The large language models have achieved superior performance on various natural language tasks. One major drawback of such approaches is they are resource-intensive in fine-tuning…
TCRA-LLM: Token Compression Retrieval Augmented Large Language Model for Inference Cost Reduction
Junyi Liu, Liangzhi Li, Tong Xiang +2
Since ChatGPT released its API for public use, the number of applications built on top of commercial large language models (LLMs) increase exponentially. One popular usage of such…