6 citations · 11 across the 7 of their papers we have counts for
9 papers
BRIDGE: Bilevel Retrieval-Credit-Aware Agentic Reinforcement Learning
Quan Xiao, Mingda Liu, Gaowen Liu +2
Agentic reinforcement learning (ARL) with verifiable rewards improves the ability of large language models (LLMs) to tackle knowledge-intensive tasks by learning to interleave sear…
Bilevel Data Curation for LLM Fine-tuning: Offline Selection and Online Self-Refining Generation
Quan Xiao, Yutong Xuan, Gaowen Liu +2
Supervised fine-tuning (SFT) datasets are critical to the downstream performance of large language models, yet they often contain low-quality or harmful question-response pairs. To…
FedHFT: Efficient Federated Finetuning with Heterogeneous Edge Clients
Fatih Ilhan, Selim Furkan Tekin, Tiansheng Huang +6
Fine-tuning pre-trained large language models (LLMs) has become a common practice for personalized natural language understanding (NLU) applications on downstream tasks and domain-…
A First-order Generative Bilevel Optimization Framework for Diffusion Models
Quan Xiao, Hui Yuan, A F M Saif +4
Diffusion models, which iteratively denoise data samples to synthesize high-quality outputs, have achieved empirical success across domains. However, optimizing these models for do…
QUOTA: Quantifying Objects with Text-to-Image Models for Any Domain
Wenfang Sun, Yingjun Du, Gaowen Liu +2
We tackle the problem of quantifying the number of objects by a generative text-to-image model. Rather than retraining such a model for each new image domain of interest, which lea…
Prompt Diffusion Robustifies Any-Modality Prompt Learning
Yingjun Du, Gaowen Liu, Yuzhang Shang +3
Foundation models enable prompt-based classifiers for zero-shot and few-shot learning. Nonetheless, the conventional method of employing fixed prompts suffers from distributional s…
A Survey on Large Language Model-Based Game Agents
Sihao Hu, Tiansheng Huang, Gaowen Liu +6
Game environments provide rich, controllable settings that stimulate many aspects of real-world complexity. As such, game agents offer a valuable testbed for exploring capabilities…
Training-Free Semantic Segmentation via LLM-Supervision
Wenfang Sun, Yingjun Du, Gaowen Liu +2
Recent advancements in open vocabulary models, like CLIP, have notably advanced zero-shot classification and segmentation by utilizing natural language for class-specific embedding…
Fast and Resource-Efficient Object Tracking on Edge Devices: A Measurement Study
Sanjana Vijay Ganesh, Yanzhao Wu, Gaowen Liu +2
Object tracking is an important functionality of edge video analytic systems and services. Multi-object tracking (MOT) detects the moving objects and tracks their locations frame b…