conftrace_

Ming Gao

38 papers · 2020–2025 · 11 conferences · across top CS/AI conferences

Achievements

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+9 more ↓ 🧭 Keyword Pioneer 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (10) 🌍 Conference Polyglot (11)
πŸƒ Academic Marathon (5) 🐝 Cross-Pollinator (7) 🌈 Renaissance Researcher (5) πŸ† Keyword Champion (2) 🀝 Dynamic Duo (17) ⚑ Prolific Year (10) πŸ—ƒοΈ Keyword Collector (166) πŸ”₯ Unstoppable (6) πŸ’Ž Century Club (38)

Conferences

EMNLP (11) ACL (6) NIPS (5) COLING (4) AAAI (3) AISTATS (2) INTERSPEECH (2) NAACL (2) CVPR (1) ICCV (1) IJCNLP (1)

Research topics

Papers

PA-RAG: RAG Alignment via Multi-Perspective Preference Optimization NAACL 2025 TransCoder: Towards Unified Transferable Code Representation Learning Inspired by Human Skills COLING 2024 Cross-model Control: Improving Multiple Large Language Models in One-time Training NIPS 2024 Unsupervised Gene-Cell Collective Representation Learning with Optimal Transport AAAI 2024 Model AI Assignments 2024 AAAI 2024 Boosting Language Models Reasoning with Chain-of-Knowledge Prompting ACL 2024 InstructGraph: Boosting Large Language Models via Graph-centric Instruction Tuning and Preference Alignment ACL 2024 Optimal estimation of Gaussian (poly)trees AISTATS 2024 Conjoin after Decompose: Improving Few-Shot Performance of Named Entity Recognition COLING 2024 Make Prompt-based Black-Box Tuning Colorful: Boosting Model Generalization from Three Orthogonal Perspectives COLING 2024 Structure-aware Fine-tuning for Code Pre-trained Models COLING 2024 Enhancing Voice Wake-Up for Dysarthria: Mandarin Dysarthria Speech Corpus Release and Customized System Design INTERSPEECH 2024 CDSD: Chinese Dysarthria Speech Database INTERSPEECH 2024 Knowledgeable In-Context Tuning: Exploring and Exploiting Factual Knowledge for In-Context Learning NAACL 2024 Uncertainty-aware Parameter-Efficient Self-training for Semi-supervised Language Understanding EMNLP 2023 Pass-Tuning: Towards Structure-Aware Parameter-Efficient Tuning for Code Representation Learning EMNLP 2023 DialCoT Meets PPO: Decomposing and Exploring Reasoning Paths in Smaller Language Models EMNLP 2023 DFRD: Data-Free Robustness Distillation for Heterogeneous Federated Learning NIPS 2023 When Gradient Descent Meets Derivative-Free Optimization: A Match Made in Black-Box Scenario ACL 2023 Uncertainty-Aware Self-Training for Low-Resource Neural Sequence Labeling AAAI 2023 GradMA: A Gradient-Memory-Based Accelerated Federated Learning With Alleviated Catastrophic Forgetting CVPR 2023 FashionKLIP: Enhancing E-Commerce Image-Text Retrieval with Fashion Multi-Modal Conceptual Knowledge Graph ACL 2023 Evaluating and Enhancing the Robustness of Code Pre-trained Models through Structure-Aware Adversarial Samples Generation EMNLP 2023 DDIT: Semantic Scene Completion via Deformable Deep Implicit Templates ICCV 2023 Optimal estimation of Gaussian DAG models AISTATS 2022 KECP: Knowledge Enhanced Contrastive Prompting for Few-shot Extractive Question Answering EMNLP 2022 Knowledge Prompting in Pre-trained Language Model for Natural Language Understanding EMNLP 2022 SpanProto: A Two-stage Span-based Prototypical Network for Few-shot Named Entity Recognition EMNLP 2022 Towards Unified Prompt Tuning for Few-shot Text Classification EMNLP 2022 ARTIST: A Transformer-based Chinese Text-to-Image Synthesizer Digesting Linguistic and World Knowledge EMNLP 2022 CAT-probing: A Metric-based Approach to Interpret How Pre-trained Models for Programming Language Attend Code Structure EMNLP 2022 A Neural Network Architecture for Program Understanding Inspired by Human Behaviors ACL 2022 Meta-Learning Adversarial Domain Adaptation Network for Few-Shot Text Classification ACL 2021 Meta-Learning Adversarial Domain Adaptation Network for Few-Shot Text Classification IJCNLP 2021 TransPrompt: Towards an Automatic Transferable Prompting Framework for Few-shot Text Classification EMNLP 2021 Efficient Bayesian network structure learning via local Markov boundary search NIPS 2021 Structure learning in polynomial time: Greedy algorithms, Bregman information, and exponential families NIPS 2021 A polynomial-time algorithm for learning nonparametric causal graphs NIPS 2020