activity
20232026
most citedAn Item is Worth a Prompt: Versatile Image Editing with Disentangled Control

1 citations · 3 across the 10 of their papers we have counts for

collaborators

10 papers

cs.LG2026

FlexRec: Adapting LLM-based Recommenders for Flexible Needs via Reinforcement Learning

Yijun Pan, Weikang Qiu, Qiyao Ma +4

Modern recommender systems must adapt to dynamic, need-specific objectives for diverse recommendation scenarios, yet most traditional recommenders are optimized for a single static…

cs.RO2026

Efficient Long-Horizon Vision-Language-Action Models via Static-Dynamic Disentanglement

Weikang Qiu, Huashuo Lei, Tinglin Huang +1

Vision-Language-Action (VLA) models have recently emerged as a promising paradigm for generalist robotic control. Built upon vision-language model (VLM) architectures, VLAs predict…

cs.CL2025★ 1 cited

RephQA: Evaluating Readability of Large Language Models in Public Health Question Answering

Weikang Qiu, Tinglin Huang, Ryan Rullo +4

Large Language Models (LLMs) hold promise in addressing complex medical problems. However, while most prior studies focus on improving accuracy and reasoning abilities, a significa…

cs.CV2025

Seeing Through the Brain: New Insights from Decoding Visual Stimuli with fMRI

Zheng Huang, Enpei Zhang, Weikang Qiu +7

Understanding how the brain encodes visual information is a central challenge in neuroscience and machine learning. A promising approach is to reconstruct visual stimuli, essential…

cs.CL2025

Beyond Correctness: Rewarding Faithful Reasoning in Retrieval-Augmented Generation

Zhichao Xu, Zongyu Wu, Yun Zhou +9

Inspired by the success of reinforcement learning (RL) in Large Language Model (LLM) training for domains like math and code, recent work has begun training LLMs to dynamically pla…

cs.LG2025★ 1 cited

Mixture-of-Personas Language Models for Population Simulation

Ngoc Bui, Hieu Trung Nguyen, Shantanu Kumar +4

Advances in Large Language Models (LLMs) paved the way for their emerging applications in various domains, such as human behavior simulations, where LLMs could augment human-genera…

q-bio.NC2025

MindLLM: A Subject-Agnostic and Versatile Model for fMRI-to-Text Decoding

Weikang Qiu, Zheng Huang, Haoyu Hu +3

Decoding functional magnetic resonance imaging (fMRI) signals into text has been a key challenge in the neuroscience community, with the potential to advance brain-computer interfa…

cs.CV2024★ 1 cited

An Item is Worth a Prompt: Versatile Image Editing with Disentangled Control

Aosong Feng, Weikang Qiu, Jinbin Bai +5

Building on the success of text-to-image diffusion models (DPMs), image editing is an important application to enable human interaction with AI-generated content. Among various edi…

q-bio.NC2023

Learning High-Order Relationships of Brain Regions

Weikang Qiu, Huangrui Chu, Selena Wang +4

Discovering reliable and informative relationships among brain regions from functional magnetic resonance imaging (fMRI) signals is essential in phenotypic predictions. Most of the…

cs.CL2023

Revisiting the Knowledge Injection Frameworks

Peng Fu, Yiming Zhang, Haobo Wang +2

In recent years, large language models (LLMs), such as GPTs, have attained great impact worldwide. However, how to adapt these LLMs to better suit the vertical domain-specific task…