Xufang Luo
24 papers · 2020–2026 · 10 venues · across top CS/AI venues
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Machine Learning
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Artificial Intelligence
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Deep Learning
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Optimization & Theory
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Reinforcement Learning
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Keywords
prompt compression
(4)
deep reinforcement learning
(4)
long context
(4)
sample efficiency
(3)
reinforcement learning
(3)
offline reinforcement learning
(3)
representation learning
(2)
sparse attention
(2)
inference optimization
(2)
position bia
(2)
large language model
(2)
domain adaptation
(1)
transfer learning
(1)
bayesian inference
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variational inference
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sequence modeling
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attention mechanism
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transformer architecture
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direct preference optimization
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function approximation
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Papers
LLM2CLIP: Powerful Language Model Unlocks Richer Cross-Modality Representation
AAAI 2026
Think with 3D: Geometric Imagination Grounded Spatial Reasoning from Limited Views
CVPR 2026
Mitigate Position Bias in LLMs via Scaling a Single Hidden States Channel
ACL 2025
Mitigating Hallucinations in Large Vision-Language Models via DPO: On-Policy Data Hold the Key
CVPR 2025
MMInference: Accelerating Pre-filling for Long-Context Visual Language Models via Modality-Aware Permutation Sparse Attention
ICML 2025
pMoE: Prompting Diverse Experts Together Wins More in Visual Adaptation
ICLR 2025
SCBench: A KV Cache-Centric Analysis of Long-Context Methods
ICLR 2025
SeCom: On Memory Construction and Retrieval for Personalized Conversational Agents
ICLR 2025
VisRL: Intention-Driven Visual Perception via Reinforced Reasoning
ICCV 2025
Addressing Signal Delay in Deep Reinforcement Learning
ICLR 2024
CNN Kernels Can Be the Best Shapelets
ICLR 2024
LLMLingua-2: Data Distillation for Efficient and Faithful Task-Agnostic Prompt Compression
ACL 2024
LongLLMLingua: Accelerating and Enhancing LLMs in Long Context Scenarios via Prompt Compression
ACL 2024
MInference 1.0: Accelerating Pre-filling for Long-Context LLMs via Dynamic Sparse Attention
NeurIPS 2024
Unified Medical Image Pre-training in Language-Guided Common Semantic Space
ECCV 2024
Adaptive Policy Learning for Offline-to-Online Reinforcement Learning
AAAI 2023
CircuitNet: A Generic Neural Network to Realize Universal Circuit Motif Modeling
ICML 2023
Data Continuity Matters: Improving Sequence Modeling with Lipschitz Regularizer
ICLR 2023
Bootstrapped Transformer for Offline Reinforcement Learning
NeurIPS 2022
Towards Applicable Reinforcement Learning: Improving the Generalization and Sample Efficiency with Policy Ensemble
IJCAI 2022
Variational oracle guiding for reinforcement learning
ICLR 2022
VRL3: A Data-Driven Framework for Visual Deep Reinforcement Learning
NeurIPS 2022
Path-BN: Towards effective batch normalization in the Path Space for ReLU networks
UAI 2021
I4R: Promoting Deep Reinforcement Learning by the Indicator for Expressive Representations
IJCAI 2020