activity
20232026
most citedDPStyler: Dynamic PromptStyler for Source-Free Domain Generalization

2 citations · 4 across the 12 of their papers we have counts for

collaborators

13 papers

cs.LG2026

Energy-Structured Low-Rank Adaptation for Continual Learning

Longhua Li, Lei Qi, Qi Tian +1

While orthogonal subspace methods try to mitigate task interference in Continual Learning (CL), they often suffer from energy diffusion across the basis, hindering knowledge compac…

cs.LG2026

Data-Aware Model Merging in the Essential Subspace for Multi-Task Knowledge Aggregation

Longhua Li, Lei Qi, Xin Geng +1

Model merging enables training-free multi-task learning by aggregating knowledge from models fine-tuned from a shared checkpoint, but their task updates can interfere. Using proxy…

cs.SE2026

iScript: A Domain-Adapted Large Language Model and Benchmark for Physical Design Tcl Script Generation

Ning Xu, Zhaoyang Zhang, Senlin Shu +10

Modern EDA flows rely heavily on Tcl scripting, yet general LLMs perform poorly in this domain due to extreme data scarcity, domain-specific semantics, and the high reliability req…

cs.LG2026

Model Merging in the Essential Subspace

Longhua Li, Lei Qi, Qi Tian +1

Model merging aims to integrate multiple task-specific fine-tuned models derived from a shared pre-trained checkpoint into a single multi-task model without additional training. De…

cs.LG2025

Stratified Knowledge-Density Super-Network for Scalable Vision Transformers

Longhua Li, Lei Qi, Xin Geng

Training and deploying multiple vision transformer (ViT) models for different resource constraints is costly and inefficient. To address this, we propose transforming a pre-trained…

cs.CV2025

One-Shot Knowledge Transfer for Scalable Person Re-Identification

Longhua Li, Lei Qi, Xin Geng

Edge computing in person re-identification (ReID) is crucial for reducing the load on central cloud servers and ensuring user privacy. Conventional compression methods for obtainin…

cs.CV2024

CLIP-DFGS: A Hard Sample Mining Method for CLIP in Generalizable Person Re-Identification

Huazhong Zhao, Lei Qi, Xin Geng

Recent advancements in pre-trained vision-language models like CLIP have shown promise in person re-identification (ReID) applications. However, their performance in generalizable…

cs.AR2024

ChipExpert: The Open-Source Integrated-Circuit-Design-Specific Large Language Model

Ning Xu, Zhaoyang Zhang, Lei Qi +17

The field of integrated circuit (IC) design is highly specialized, presenting significant barriers to entry and research and development challenges. Although large language models…

cs.CV2024★ 2 cited

DPStyler: Dynamic PromptStyler for Source-Free Domain Generalization

Yunlong Tang, Yuxuan Wan, Lei Qi +1

Source-Free Domain Generalization (SFDG) aims to develop a model that works for unseen target domains without relying on any source domain. Research in SFDG primarily bulids upon t…

cs.CV2024

A SAM-guided Two-stream Lightweight Model for Anomaly Detection

Chenghao Li, Lei Qi, Xin Geng

In industrial anomaly detection, model efficiency and mobile-friendliness become the primary concerns in real-world applications. Simultaneously, the impressive generalization capa…

cs.CL2024★ 1 cited

OlympiadBench: A Challenging Benchmark for Promoting AGI with Olympiad-Level Bilingual Multimodal Scientific Problems

Chaoqun He, Renjie Luo, Yuzhuo Bai +11

Recent advancements have seen Large Language Models (LLMs) and Large Multimodal Models (LMMs) surpassing general human capabilities in various tasks, approaching the proficiency le…

cs.CV2023

DoubleAUG: Single-domain Generalized Object Detector in Urban via Color Perturbation and Dual-style Memory

Lei Qi, Peng Dong, Tan Xiong +2

Object detection in urban scenarios is crucial for autonomous driving in intelligent traffic systems. However, unlike conventional object detection tasks, urban-scene images vary g…

cs.LG2023★ 1 cited

Scalable Label Distribution Learning for Multi-Label Classification

Xingyu Zhao, Yuexuan An, Lei Qi +1

Multi-label classification (MLC) refers to the problem of tagging a given instance with a set of relevant labels. Most existing MLC methods are based on the assumption that the cor…