Sheng Zha
20 papers · 2018–2025 · 9 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (7) 🌍 Conference Polyglot (9) 🌉 Interdisciplinary Bridge 🧭 Keyword Pioneer 🐣 Hot Topic Early Bird
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Conference Polyglot
(9)
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(7)
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(11)
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(2)
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(82)
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Conferences
EMNLP (5)
NIPS (4)
ACL (3)
ICML (2)
NAACL (2)
AAAI (1)
ECCV (1)
IJCNLP (1)
JMLR (1)
Top co-authors
Research topics
Keywords
large language model
(4)
transfer learning
(3)
code completion
(3)
differential privacy
(3)
code language model
(2)
computer vision
(2)
instruction following
(2)
language model
(2)
gradient clipping
(2)
natural language processing
(2)
text classification
(2)
multi-task learning
(2)
deep learning
(2)
code generation
(2)
program synthesis
(2)
distribution shift
(2)
foundation model
(2)
model calibration
(1)
adversarial robustness
(1)
hyperparameter optimization
(1)
Papers
Sequence-level Large Language Model Training with Contrastive Preference Optimization
NAACL 2025
Extreme Miscalibration and the Illusion of Adversarial Robustness
ACL 2024
Fine-tuning Language Models for Joint Rewriting and Completion of Code with Potential Bugs
ACL 2024
Differentially Private Bias-Term Fine-tuning of Foundation Models
ICML 2024
DEM: Distribution Edited Model for Training with Mixed Data Distributions
EMNLP 2024
Pre-training Differentially Private Models with Limited Public Data
NIPS 2024
HyTrel: Hypergraph-enhanced Tabular Data Representation Learning
NIPS 2023
Large Language Models of Code Fail at Completing Code with Potential Bugs
NIPS 2023
Automatic Clipping: Differentially Private Deep Learning Made Easier and Stronger
NIPS 2023
Better Context Makes Better Code Language Models: A Case Study on Function Call Argument Completion
AAAI 2023
Efficient Long-Range Transformers: You Need to Attend More, but Not Necessarily at Every Layer
EMNLP 2023
Differentially Private Optimization on Large Model at Small Cost
ICML 2023
Meta-learning via Language Model In-context Tuning
ACL 2022
Exploring the Role of Task Transferability in Large-Scale Multi-Task Learning
NAACL 2022
Distiller: A Systematic Study of Model Distillation Methods in Natural Language Processing
EMNLP 2021
GluonCV and GluonNLP: Deep Learning in Computer Vision and Natural Language Processing
JMLR 2020
Dive into Deep Learning for Natural Language Processing
IJCNLP 2019
Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual
EMNLP 2019
Dive into Deep Learning for Natural Language Processing
EMNLP 2019
Question Type Guided Attention in Visual Question Answering
ECCV 2018