Peng Lu
20 papers · 2019–2026 · 10 conferences · across top CS/AI conferences
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ACL (4)
EMNLP (4)
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ICML (2)
NAACL (2)
AAAI (1)
ICCV (1)
ICLR (1)
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Keywords
large language model
(3)
knowledge distillation
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label smoothing
(3)
multimodal learning
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language model
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model compression
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model efficiency
(2)
label regularization
(2)
sequence labeling
(1)
machine translation
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pose estimation
(1)
named entity recognition
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multi-task learning
(1)
autonomous driving
(1)
attention mechanism
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transfer learning
(1)
efficient computing
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object tracking
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object detection
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human pose estimation
(1)
Papers
Investigating the Multilingual Calibration Effects of Language Model Instruction Tuning
EACL 2026
MultiFinBen: Benchmarking Large Language Models for Multilingual and Multimodal Financial Application
ACL 2026
MATCH: Modulating Attention via In-Context Retrieval for Long-Context Transformers
ACL 2026
Novel View Synthesis Under Large-Deviation Viewpoint for Autonomous Driving
AAAI 2025
Can Machines Understand Composition? Dataset and Benchmark for Photographic Image Composition Embedding and Understanding
CVPR 2025
ZETA: Leveraging $Z$-order Curves for Efficient Top-$k$ Attention
ICLR 2025
Calibrated Language Models and How to Find Them with Label Smoothing
ICML 2025
ReGLA: Refining Gated Linear Attention
NAACL 2025
Empower Programmable Pipeline for Advanced Stateful Packet Processing
NSDI 2024
Draft on the Fly: Adaptive Self-Speculative Decoding using Cosine Similarity
EMNLP 2024
RTMO: Towards High-Performance One-Stage Real-Time Multi-Person Pose Estimation
CVPR 2024
VinT-6D: A Large-Scale Object-in-hand Dataset from Vision, Touch and Proprioception
ICML 2024
Resonance RoPE: Improving Context Length Generalization of Large Language Models
ACL 2024
Efficient Classification of Long Documents via State-Space Models
EMNLP 2023
LABO: Towards Learning Optimal Label Regularization via Bi-level Optimization
ACL 2023
Do we need Label Regularization to Fine-tune Pre-trained Language Models?
EACL 2023
Improving Generalization of Pre-trained Language Models via Stochastic Weight Averaging
EMNLP 2022
RW-KD: Sample-wise Loss Terms Re-Weighting for Knowledge Distillation
EMNLP 2021
SC-LSTM: Learning Task-Specific Representations in Multi-Task Learning for Sequence Labeling
NAACL 2019
Learning Aberrance Repressed Correlation Filters for Real-Time UAV Tracking
ICCV 2019