Yu Bai
65 papers · 2019–2026 · 17 conferences · across top CS/AI conferences
Achievements
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πΊοΈ Taxonomy Completionist (11) π§ Keyword Pioneer π Interdisciplinary Bridge π Renaissance Researcher (5) π Conference Polyglot (16)
π
Interdisciplinary Bridge
πΊοΈ
Taxonomy Completionist
(11)
π§
Keyword Pioneer
π
Grand Slam
π
Triple Crown
π€
Dynamic Duo
(15)
π¬
Deep Specialist
(12)
π§¬
Topic Evolution
β‘
Prolific Year
(12)
ποΈ
Keyword Collector
(218)
β
The Questioner
(6)
π
Century Club
(61)
π₯
Unstoppable
(7)
Conferences
NIPS (14)
ICLR (12)
ICML (10)
AAAI (5)
ACL (5)
INTERSPEECH (3)
EMNLP (3)
COLING (3)
CVPR (2)
ECCV (1)
EACL (1)
COLT (1)
IJCAI (1)
IJCNLP (1)
AISTATS (1)
NSDI (1)
UAI (1)
Top co-authors
Research topics
Keywords
sample complexity
(9)
markov game
(5)
nash equilibrium
(5)
few-shot learning
(5)
abstractive summarization
(4)
regret minimization
(4)
offline reinforcement learning
(4)
multi-agent reinforcement learning
(3)
large language model
(3)
extensive-form game
(3)
zero-shot learning
(3)
foundation model
(3)
automatic speech recognition
(3)
policy optimization
(3)
in-context learning
(3)
regret bound
(3)
game theory
(3)
attention mechanism
(3)
correlated equilibrium
(3)
multi-task learning
(2)
Papers
EduBench: A Comprehensive Benchmarking Dataset for Evaluating Large Language Models in Diverse Educational Scenarios
ACL 2026
MMRA: A Benchmark for Evaluating Multi-Granularity and Multi-Image Relational Association Capabilities in Large Visual Language Models
EACL 2026
Explain the Synth: Interpretable Evaluation of LLM Data Synthesis
ACL 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
Resolving Packets from Counters: Enabling Multi-scale Network Traffic Super Resolution via Composable Large Traffic Model
NSDI 2025
VCRMNER: Visual Cue Refinement in Multimodal NER using CLIP Prompts
COLING 2025
Reasoning Knowledge Filter for Logical Table-to-Text Generation
COLING 2025
Text2Data: Low-Resource Data Generation with Textual Control
AAAI 2025
Excluding the Impossible for Open Vocabulary Semantic Segmentation
AAAI 2025
How Far Can In-Context Alignment Go? Exploring the State of In-Context Alignment
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
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
Sample-Efficient Learning of POMDPs with Multiple Observations In Hindsight
ICLR 2024
An ASR-enabled Reading Tutor: Investigating Feedback to Optimize Interaction for Learning to Read
INTERSPEECH 2023
Improved Online Conformal Prediction via Strongly Adaptive Online Learning
ICML 2023
What can a Single Attention Layer Learn? A Study Through the Random Features Lens
NIPS 2023
The Role of Coverage in Online Reinforcement Learning
ICLR 2023
Learning Rationalizable Equilibria in Multiplayer Games
ICLR 2023
Breaking the Curse of Multiagency: Provably Efficient Decentralized Multi-Agent RL with Function Approximation
COLT 2023
Offline Learning in Markov Games with General Function Approximation
ICML 2023
Partially Observable RL with B-Stability: Unified Structural Condition and Sharp Sample-Efficient Algorithms
ICLR 2023
Transformers as Statisticians: Provable In-Context Learning with In-Context Algorithm Selection
NIPS 2023
Efficient RL with Impaired Observability: Learning to Act with Delayed and Missing State Observations
NIPS 2023
Lower Bounds for Learning in Revealing POMDPs
ICML 2023
DePA: Improving Non-autoregressive Translation with Dependency-Aware Decoder
ACL 2023
Identifying good directions to escape the NTK regime and efficiently learn low-degree plus sparse polynomials
NIPS 2022
Sample-Efficient Learning of Correlated Equilibria in Extensive-Form Games
NIPS 2022
Policy Optimization for Markov Games: Unified Framework and Faster Convergence
NIPS 2022
Efficient Phi-Regret Minimization in Extensive-Form Games via Online Mirror Descent
NIPS 2022
PSP: Pre-trained Soft Prompts for Few-Shot Abstractive Summarization
COLING 2022
Conformal Predictor for Improving Zero-Shot Text Classification Efficiency
EMNLP 2022
When Can We Learn General-Sum Markov Games with a Large Number of Players Sample-Efficiently?
ICLR 2022
Efficient and Differentiable Conformal Prediction with General Function Classes
ICLR 2022
Near-Optimal Learning of Extensive-Form Games with Imperfect Information
ICML 2022
Stage-wise Stylistic Headline Generation: Style Generation and Summarized Content Insertion
IJCAI 2022
The Effects of Implicit and Explicit Feedback in an ASR-based Reading Tutor for Dutch First-graders
INTERSPEECH 2022
Local calibration: metrics and recalibration
UAI 2022
How Important is the Train-Validation Split in Meta-Learning?
ICML 2021
Donβt Just Blame Over-parametrization for Over-confidence: Theoretical Analysis of Calibration in Binary Classification
ICML 2021
Policy Finetuning: Bridging Sample-Efficient Offline and Online Reinforcement Learning
NIPS 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
Understanding the Under-Coverage Bias in Uncertainty Estimation
NIPS 2021
Near-Optimal Provable Uniform Convergence in Offline Policy Evaluation for Reinforcement Learning
AISTATS 2021
Cross-Lingual Abstractive Summarization with Limited Parallel Resources
ACL 2021
Exploring Explainable Selection to Control Abstractive Summarization
AAAI 2021
Sample-Efficient Learning of Stackelberg Equilibria in General-Sum Games
NIPS 2021
Near-Optimal Offline Reinforcement Learning via Double Variance Reduction
NIPS 2021
Cross-Lingual Abstractive Summarization with Limited Parallel Resources
IJCNLP 2021
Provable Self-Play Algorithms for Competitive Reinforcement Learning
ICML 2020
ASR-Based Evaluation and Feedback for Individualized Reading Practice
INTERSPEECH 2020
Towards Understanding Hierarchical Learning: Benefits of Neural Representations
NIPS 2020
Near-Optimal Reinforcement Learning with Self-Play
NIPS 2020
Beyond Linearization: On Quadratic and Higher-Order Approximation of Wide Neural Networks
ICLR 2020
Subgradient Descent Learns Orthogonal Dictionaries
ICLR 2019
Approximability of Discriminators Implies Diversity in GANs
ICLR 2019
Provably Efficient Q-Learning with Low Switching Cost
NIPS 2019
ProxQuant: Quantized Neural Networks via Proximal Operators
ICLR 2019