5 citations · 6 across the 29 of their papers we have counts for
7 papers · 1 filter
Weak type estimates for Riesz transforms of elliptic operators and magnetic Schrödinger operators
El Maati Ouhabaz
Let be a complete Riemannian manifold and define a magnetic Schrödinger operator $\LL = ({\bf d}+ iA)^*({\bf d}+iA) + V$ where is a real -differential form in $L^2_{loc}…
EvoPolicyGym: Evaluating Autonomous Policy Evolution in Interactive Environments
Zhilin Wang, Han Song, Runzhe Zhan +13
Autonomous agents are increasingly expected to improve executable policies through feedback, yet existing evaluations often collapse this process into a final score or confound it…
On the Geometry of On-Policy Distillation
Zhennan Shen, Yanshu Li, Qingyu Yin +6
On-policy distillation (OPD) is increasingly used to improve large language model reasoning, but its training dynamics remain poorly understood. We characterize the trajectory of O…
DeCo-DETR: Decoupled Cognition DETR for efficient Open-Vocabulary Object Detection
Siheng Wang, Yanshu Li, Bohan Hu +12
Open-vocabulary object detection (OVOD) enables models to recognize objects beyond predefined categories, but existing approaches remain limited in practical deployment. On the one…
Personalize Your Large Vision-language Models With In-context Prompt Tuning
Yanshu Li, Jiaqian Li, Kuai Yu +4
Large vision-language models (LVLMs) have demonstrated strong general multimodal capability and are increasingly deployed in downstream systems. This trend has driven growing inter…
Not All Directions Matter: Towards Structured and Task-Aware Low-Rank Model Adaptation
Xi Xiao, Chenrui Ma, Yunbei Zhang +7
Low-Rank Adaptation (LoRA) has become a cornerstone of parameter-efficient fine-tuning (PEFT). Yet, its efficacy is hampered by two fundamental limitations: semantic drift, by trea…
Steering Vector Fields for Context-Aware Inference-Time Control in Large Language Models
Jiaqian Li, Yanshu Li, Kuan-Hao Huang
Steering vectors (SVs) offer a lightweight way to control large language models (LLMs) at inference time by shifting hidden activations, providing a practical middle ground between…