8 papers
Rep2Skill: Representation-Guided Skill Self-Evolution for LLM Agents
Kaixing Zhang, Changming Li, Yingdong Shi +5
Textual skills enable large language model (LLM) based agents to accumulate reusable procedural knowledge without updating model parameters. Yet existing skill evolution remains la…
OPMD: On-Policy Mechanism Distillation Beyond Output Supervision
Yingdong Shi, Zhihong Li, Changming Li +3
On-policy distillation (OPD) improves language-model by supervising a student on prefixes sampled from its own policy, but its supervision remains confined to the output space. Con…
UniSteer: Text-Guided Flow Matching in Activation Space for Versatile LLM Steering
Yingdong Shi, Ruiming Zhang, Changming Li +4
Activation-based control steers large language models (LLMs) by intervening on their internal representations during inference, and has emerged as an effective paradigm for control…
SceneReVis: A Self-Reflective Vision-Grounded Framework for 3D Indoor Scene Synthesis via Multi-Turn RL
Yang Zhao, Shizhao Sun, Meisheng Zhang +3
Current one-pass 3D scene synthesis methods often suffer from spatial hallucinations, such as collisions, due to a lack of deliberative reasoning. To bridge this gap, we introduce…
Interpreting and Controlling LLM Reasoning through Integrated Policy Gradient
Changming Li, Kaixing Zhang, Haoyun Xu +4
Large language models (LLMs) demonstrate strong reasoning abilities in solving complex real-world problems. Yet, the internal mechanisms driving these complex reasoning behaviors r…
DesignAsCode: Bridging Structural Editability and Visual Fidelity in Graphic Design Generation
Ziyuan Liu, Shizhao Sun, Danqing Huang +5
Graphic design generation demands a delicate balance between high visual fidelity and fine-grained structural editability. However, existing approaches typically bifurcate into eit…
Discovering Influential Neuron Path in Vision Transformers
Yifan Wang, Yifei Liu, Yingdong Shi +5
Vision Transformer models exhibit immense power yet remain opaque to human understanding, posing challenges and risks for practical applications. While prior research has attempted…
Dissecting and Mitigating Diffusion Bias via Mechanistic Interpretability
Yingdong Shi, Changming Li, Yifan Wang +5
Diffusion models have demonstrated impressive capabilities in synthesizing diverse content. However, despite their high-quality outputs, these models often perpetuate social biases…