Felix Yu
25 papers · 2013–2025 · 8 conferences · across top CS/AI conferences
Achievements
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🌍 Conference Polyglot (8) 🐣 Hot Topic Early Bird 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🏃 Academic Marathon (12)
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(8)
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(17)
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(25)
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Conferences
ICML (7)
ICLR (6)
ACL (3)
AISTATS (3)
EMNLP (2)
NIPS (2)
CVPR (1)
IJCNLP (1)
Top co-authors
Research topics
Keywords
large language model
(3)
negative sampling
(2)
autoregressive sampling
(2)
large output space
(2)
language generation
(2)
federated learning
(2)
frame semantics
(2)
lexical constraint
(2)
bidirectional context
(2)
text infilling
(2)
representation learning
(2)
weakly supervised learning
(1)
compressed sensing
(1)
knowledge distillation
(1)
optimal transport
(1)
image retrieval
(1)
differential privacy
(1)
similarity search
(1)
mean estimation
(1)
embedding space
(1)
Papers
Better autoregressive regression with LLMs via regression-aware fine-tuning
ICLR 2025
Large Language Models are Interpretable Learners
ICLR 2025
LoRA Done RITE: Robust Invariant Transformation Equilibration for LoRA Optimization
ICLR 2025
Efficient and Asymptotically Unbiased Constrained Decoding for Large Language Models
AISTATS 2025
Regression Aware Inference with LLMs
EMNLP 2024
Automatic Engineering of Long Prompts
ACL 2024
Two-stage LLM Fine-tuning with Less Specialization and More Generalization
ICLR 2024
Serving Graph Compression for Graph Neural Networks
ICLR 2023
Large Language Models with Controllable Working Memory
ACL 2023
SpecTr: Fast Speculative Decoding via Optimal Transport
NIPS 2023
FedDM: Iterative Distribution Matching for Communication-Efficient Federated Learning
CVPR 2023
The Lazy Neuron Phenomenon: On Emergence of Activation Sparsity in Transformers
ICLR 2023
Correlated Quantization for Distributed Mean Estimation and Optimization
ICML 2022
InFillmore: Frame-Guided Language Generation with Bidirectional Context
IJCNLP 2021
InFillmore: Frame-Guided Language Generation with Bidirectional Context
ACL 2021
RankDistil: Knowledge Distillation for Ranking
AISTATS 2021
Disentangling Sampling and Labeling Bias for Learning in Large-output Spaces
ICML 2021
Semantic Label Smoothing for Sequence to Sequence Problems
EMNLP 2020
Federated Learning with Only Positive Labels
ICML 2020
Learning a Compressed Sensing Measurement Matrix via Gradient Unrolling
ICML 2019
Stochastic Negative Mining for Learning with Large Output Spaces
AISTATS 2019
Loss Decomposition for Fast Learning in Large Output Spaces
ICML 2018
Multiscale Quantization for Fast Similarity Search
NIPS 2017
Circulant Binary Embedding
ICML 2014
\proptoSVM for Learning with Label Proportions
ICML 2013