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Yufeng Zhang

22 papers · 2019–2025 · 11 conferences · across top CS/AI conferences

Achievements

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+10 more ↓ 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (11) πŸŒ‰ Interdisciplinary Bridge πŸƒ Academic Marathon (6) 🐝 Cross-Pollinator (13)
🧭 Keyword Pioneer 🌍 Conference Polyglot (11) πŸƒ Academic Marathon (6) 🀝 Dynamic Duo (10) πŸ† Grand Slam πŸ”₯ Unstoppable (7) πŸ’Ž Century Club (22) ⚑ Prolific Year (7) ❓ The Questioner (2) πŸ—ƒοΈ Keyword Collector (103)

Conferences

ICML (5) NIPS (4) ACL (3) AAAI (2) AISTATS (2) COLING (1) CVPR (1) ECCV (1) EMNLP (1) ICCV (1) ICLR (1)

Top co-authors

Zhaoran Wang (10) Zhuoran Yang (9) Qi Cai (3) Zeyu Cui (2) Hang Yu (2) Weiyao Lin (2) Jian Yin (2) Zhihan Liu (2) Shu Wu (2) Qinliang Su (2)

Keywords

offline reinforcement learning (3) policy optimization (3) graph neural network (3) reinforcement learning (2) representation learning (2) large language model (2) neural network (2) temporal-difference learning (2) generative adversarial imitation learning (2) linear function approximation (2) imitation learning (1) few-shot learning (1) sample efficiency (1) mean field theory (1) q-learning (1) contrastive learning (1) multivariate gaussian (1) text classification (1) function approximation (1) temporal difference learning (1)

Papers

Reward-Augmented Data Enhances Direct Preference Alignment of LLMs ICML 2025 Enhancing Chain of Thought Prompting in Large Language Models via Reasoning Patterns AAAI 2025 DavIR: Data Selection via Implicit Reward for Large Language Models ACL 2025 What and How does In-Context Learning Learn? Bayesian Model Averaging, Parameterization, and Generalization AISTATS 2025 Detecting Emotional Incongruity of Sarcasm by Commonsense Reasoning COLING 2025 Agent-in-the-Loop: A Data Flywheel for Continuous Improvement in LLM-based Customer Support EMNLP 2025 MCOP: Multi-UAV Collaborative Occupancy Prediction ICCV 2025 Finite-State Autoregressive Entropy Coding for Efficient Learned Lossless Compression ICLR 2024 BaSIC: BayesNet Structure Learning for Computational Scalable Neural Image Compression ECCV 2024 Domain Adaptation for Subjective Induction Questions Answering on Products by Adversarial Disentangled Learning ACL 2024 On the Properties of Kullback-Leibler Divergence Between Multivariate Gaussian Distributions NIPS 2023 Learning from Demonstration: Provably Efficient Adversarial Policy Imitation with Linear Function Approximation ICML 2022 Provably Efficient Offline Reinforcement Learning for Partially Observable Markov Decision Processes ICML 2022 Provably Efficient Actor-Critic for Risk-Sensitive and Robust Adversarial RL: A Linear-Quadratic Case AISTATS 2021 A Graph-based Relevance Matching Model for Ad-hoc Retrieval AAAI 2021 Infinite-Dimensional Optimization for Zero-Sum Games via Variational Transport ICML 2021 Wasserstein Flow Meets Replicator Dynamics: A Mean-Field Analysis of Representation Learning in Actor-Critic NIPS 2021 Offline Constrained Multi-Objective Reinforcement Learning via Pessimistic Dual Value Iteration NIPS 2021 Every Document Owns Its Structure: Inductive Text Classification via Graph Neural Networks ACL 2020 Can Temporal-Difference and Q-Learning Learn Representation? A Mean-Field Theory NIPS 2020 Generative Adversarial Imitation Learning with Neural Network Parameterization: Global Optimality and Convergence Rate ICML 2020 Unified Visual-Semantic Embeddings: Bridging Vision and Language With Structured Meaning Representations CVPR 2019