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Yu Bai

63 papers · 2019–2026 · 17 conferences · across top CS/AI conferences

Achievements

πŸƒ Academic Marathon (6) 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (16) 🐝 Cross-Pollinator (9) 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (11) 🧭 Keyword Pioneer πŸ† Grand Slam πŸ‘‘ Triple Crown 🀝 Dynamic Duo (15) πŸ”¬ Deep Specialist (12) 🧬 Topic Evolution ⚑ Prolific Year (12) πŸ—ƒοΈ Keyword Collector (218) ❓ The Questioner (6) πŸ’Ž Century Club (61) πŸ”₯ Unstoppable (7)

Conferences

NIPS (14) ICLR (12) ICML (10) AAAI (5) INTERSPEECH (3) EMNLP (3) COLING (3) ACL (3) CVPR (2) EACL (1) ECCV (1) COLT (1) IJCAI (1) IJCNLP (1) AISTATS (1) NSDI (1) UAI (1)

Top co-authors

Huan Wang (15) Caiming Xiong (15) Song Mei (14) Yang Gao (10) Chi Jin (8) Heyan Huang (8) Minshuo Chen (4) Tiancheng Yu (4) Yu-Xiang Wang (4) Nan Jiang (4)

Research topics

Education (2)

Keywords

sample complexity (9) few-shot learning (5) markov game (5) nash equilibrium (5) regret minimization (4) abstractive summarization (4) offline reinforcement learning (4) multi-agent reinforcement learning (3) extensive-form game (3) zero-shot learning (3) foundation model (3) automatic speech recognition (3) in-context learning (3) regret bound (3) correlated equilibrium (3) policy optimization (3) game theory (3) attention mechanism (3) multi-task learning (2) neural tangent kernel (2)

Papers

MMRA: A Benchmark for Evaluating Multi-Granularity and Multi-Image Relational Association Capabilities in Large Visual Language Models EACL 2026
Identifying and Analyzing Performance-Critical Tokens in Large Language Models AAAI 2026
TopV: Compatible Token Pruning with Inference Time Optimization for Fast and Low-Memory Multimodal Vision Language Model CVPR 2025
VCRMNER: Visual Cue Refinement in Multimodal NER using CLIP Prompts COLING 2025
Reasoning Knowledge Filter for Logical Table-to-Text Generation COLING 2025
Excluding the Impossible for Open Vocabulary Semantic Segmentation AAAI 2025
Text2Data: Low-Resource Data Generation with Textual Control AAAI 2025
Resolving Packets from Counters: Enabling Multi-scale Network Traffic Super Resolution via Composable Large Traffic Model NSDI 2025
How Far Can In-Context Alignment Go? Exploring the State of In-Context Alignment EMNLP 2024
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight ICLR 2024
Is Inverse Reinforcement Learning Harder than Standard Reinforcement Learning? A Theoretical Perspective ICML 2024
Collaborative Consortium of Foundation Models for Open-World Few-Shot Learning AAAI 2024
Fundamental Capabilities of Large Language Models and their Applications in Domain Scenarios: A Survey ACL 2024
DeIL: Direct-and-Inverse CLIP for Open-World Few-Shot Learning CVPR 2024
Norma: A Noise Robust Memory-Augmented Framework for Whole Slide Image Classification ECCV 2024
CItruS: Chunked Instruction-aware State Eviction for Long Sequence Modeling EMNLP 2024
Transformers as Decision Makers: Provable In-Context Reinforcement Learning via Supervised Pretraining ICLR 2024
How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations ICLR 2024
What can a Single Attention Layer Learn? A Study Through the Random Features Lens NIPS 2023
DePA: Improving Non-autoregressive Translation with Dependency-Aware Decoder ACL 2023
Breaking the Curse of Multiagency: Provably Efficient Decentralized Multi-Agent RL with Function Approximation COLT 2023
Learning Rationalizable Equilibria in Multiplayer Games ICLR 2023
The Role of Coverage in Online Reinforcement Learning ICLR 2023
Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms ICLR 2023
Offline Learning in Markov Games with General Function Approximation ICML 2023
An ASR-enabled Reading Tutor: Investigating Feedback to Optimize Interaction for Learning to Read INTERSPEECH 2023
Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations NIPS 2023
Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection NIPS 2023
Lower Bounds for Learning in Revealing POMDPs ICML 2023
Improved Online Conformal Prediction via Strongly Adaptive Online Learning ICML 2023
Near-Optimal Learning of Extensive-Form Games with Imperfect Information ICML 2022
The Effects of Implicit and Explicit Feedback in an ASR-based Reading Tutor for Dutch First-graders INTERSPEECH 2022
When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently? ICLR 2022
Sample-Efficient Learning of Correlated Equilibria in Extensive-Form Games NIPS 2022
PSP: Pre-trained Soft Prompts for Few-Shot Abstractive Summarization COLING 2022
Efficient Phi-Regret Minimization in Extensive-Form Games via Online Mirror Descent NIPS 2022
Policy Optimization for Markov Games: Unified Framework and Faster Convergence NIPS 2022
Local calibration: metrics and recalibration UAI 2022
Efficient and Differentiable Conformal Prediction with General Function Classes ICLR 2022
Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials NIPS 2022
Stage-wise Stylistic Headline Generation: Style Generation and Summarized Content Insertion IJCAI 2022
Conformal Predictor for Improving Zero-Shot Text Classification Efficiency EMNLP 2022
Cross-Lingual Abstractive Summarization with Limited Parallel Resources IJCNLP 2021
Near-Optimal Offline Reinforcement Learning via Double Variance Reduction NIPS 2021
Understanding the Under-Coverage Bias in Uncertainty Estimation NIPS 2021
Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games NIPS 2021
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning NIPS 2021
Exploring Explainable Selection to Control Abstractive Summarization AAAI 2021
Cross-Lingual Abstractive Summarization with Limited Parallel Resources ACL 2021
Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning AISTATS 2021
How Important is the Train-Validation Split in Meta-Learning? ICML 2021
Don’t Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification ICML 2021
A Sharp Analysis of Model-based Reinforcement Learning with Self-Play ICML 2021
Exact Gap between Generalization Error and Uniform Convergence in Random Feature Models ICML 2021
Provable Self-Play Algorithms for Competitive Reinforcement Learning ICML 2020
ASR-Based Evaluation and Feedback for Individualized Reading Practice INTERSPEECH 2020
Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks ICLR 2020
Towards Understanding Hierarchical Learning: Benefits of Neural Representations NIPS 2020
Near-Optimal Reinforcement Learning with Self-Play NIPS 2020
Provably Efficient Q-Learning with Low Switching Cost NIPS 2019
ProxQuant: Quantized Neural Networks via Proximal Operators ICLR 2019
Subgradient Descent Learns Orthogonal Dictionaries ICLR 2019
Approximability of Discriminators Implies Diversity in GANs ICLR 2019