Yitao Liang

According to our database1, Yitao Liang authored at least 52 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

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Bibliography

2024
ROCKET-1: Master Open-World Interaction with Visual-Temporal Context Prompting.
CoRR, 2024

Low-Dimension-to-High-Dimension Generalization And Its Implications for Length Generalization.
CoRR, 2024

Mars: Situated Inductive Reasoning in an Open-World Environment.
CoRR, 2024

QCircuitNet: A Large-Scale Hierarchical Dataset for Quantum Algorithm Design.
CoRR, 2024

TFG: Unified Training-Free Guidance for Diffusion Models.
CoRR, 2024

OmniJARVIS: Unified Vision-Language-Action Tokenization Enables Open-World Instruction Following Agents.
CoRR, 2024

CLoG: Benchmarking Continual Learning of Image Generation Models.
CoRR, 2024

Semantic Loss Functions for Neuro-Symbolic Structured Prediction.
CoRR, 2024

RAT: Retrieval Augmented Thoughts Elicit Context-Aware Reasoning in Long-Horizon Generation.
CoRR, 2024

DIGIC: Domain Generalizable Imitation Learning by Causal Discovery.
CoRR, 2024

Selecting Large Language Model to Fine-tune via Rectified Scaling Law.
Proceedings of the Forty-first International Conference on Machine Learning, 2024

GROOT: Learning to Follow Instructions by Watching Gameplay Videos.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Neural-Symbolic Recursive Machine for Systematic Generalization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

RulE: Knowledge Graph Reasoning with Rule Embedding.
Proceedings of the Findings of the Association for Computational Linguistics, 2024

ProAgent: Building Proactive Cooperative Agents with Large Language Models.
Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023
Effective long-term tracking with contrast optimizer.
Mach. Vis. Appl., July, 2023

Semantic Loss Functions for Neuro-Symbolic Structured Prediction.
Proceedings of the Compendium of Neurosymbolic Artificial Intelligence, 2023

JARVIS-1: Open-World Multi-task Agents with Memory-Augmented Multimodal Language Models.
CoRR, 2023

Expressive Modeling Is Insufficient for Offline RL: A Tractable Inference Perspective.
CoRR, 2023

MCU: A Task-centric Framework for Open-ended Agent Evaluation in Minecraft.
CoRR, 2023

ProAgent: Building Proactive Cooperative AI with Large Language Models.
CoRR, 2023

Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners.
CoRR, 2023

Describe, Explain, Plan and Select: Interactive Planning with Large Language Models Enables Open-World Multi-Task Agents.
CoRR, 2023

Describe, Explain, Plan and Select: Interactive Planning with LLMs Enables Open-World Multi-Task Agents.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Understanding the Distillation Process from Deep Generative Models to Tractable Probabilistic Circuits.
Proceedings of the International Conference on Machine Learning, 2023

SQA3D: Situated Question Answering in 3D Scenes.
Proceedings of the Eleventh International Conference on Learning Representations, 2023

Open-World Multi-Task Control Through Goal-Aware Representation Learning and Adaptive Horizon Prediction.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

Out-of-Distribution Generalization by Neural-Symbolic Joint Training.
Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022
RulE: Neural-Symbolic Knowledge Graph Reasoning with Rule Embedding.
CoRR, 2022

Efficient Meta Reinforcement Learning for Preference-based Fast Adaptation.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021
VineMap: a metaphor visualization method for public opinion hierarchy from text data.
J. Vis., 2021

Towards an Interpretable Latent Space in Structured Models for Video Prediction.
CoRR, 2021

An electrochemical immunosensor for global DNA methylation determination using magnetic bead-based enrichment and enzymatic amplification.
Proceedings of the 2021 IEEE Sensors, Sydney, Australia, October 31 - Nov. 3, 2021, 2021

Juice: A Julia Package for Logic and Probabilistic Circuits.
Proceedings of the Thirty-Fifth AAAI Conference on Artificial Intelligence, 2021

2020
Semantic and Generalized Entropy Loss Functions for Semi-Supervised Deep Learning.
Entropy, 2020

Handling Missing Data in Decision Trees: A Probabilistic Approach.
CoRR, 2020

On Effective Parallelization of Monte Carlo Tree Search.
CoRR, 2020

Au nanoflowers modified magnetic and flexible biosensor for bisulfite-free HCC global DNA methylation detection.
Proceedings of the 2020 IEEE Sensors, Rotterdam, The Netherlands, October 25-28, 2020, 2020

SAM: Squeeze-and-Mimic Networks for Conditional Visual Driving Policy Learning.
Proceedings of the 4th Conference on Robot Learning, 2020

Off-Policy Deep Reinforcement Learning with Analogous Disentangled Exploration.
Proceedings of the 19th International Conference on Autonomous Agents and Multiagent Systems, 2020

2019
LaTeS: Latent Space Distillation for Teacher-Student Driving Policy Learning.
CoRR, 2019

On Tractable Computation of Expected Predictions.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

What to Expect of Classifiers? Reasoning about Logistic Regression with Missing Features.
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

A 3D Pt nanoflowers decorated micro-needle tip for in situ detection of cellular ATP release.
Proceedings of the 2019 IEEE SENSORS, Montreal, QC, Canada, October 27-30, 2019, 2019

Learning Logistic Circuits.
Proceedings of the Thirty-Third AAAI Conference on Artificial Intelligence, 2019

2018
Horizon: Facebook's Open Source Applied Reinforcement Learning Platform.
CoRR, 2018

Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing.
CoRR, 2018

Inference Aided Reinforcement Learning for Incentive Mechanism Design in Crowdsourcing.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

A Semantic Loss Function for Deep Learning with Symbolic Knowledge.
Proceedings of the 35th International Conference on Machine Learning, 2018

2017
An application of optimization method for storyline based on cluster analysis.
Proceedings of the 10th International Symposium on Visual Information Communication and Interaction, 2017

Learning the Structure of Probabilistic Sentential Decision Diagrams.
Proceedings of the Thirty-Third Conference on Uncertainty in Artificial Intelligence, 2017

2016
State of the Art Control of Atari Games Using Shallow Reinforcement Learning.
Proceedings of the 2016 International Conference on Autonomous Agents & Multiagent Systems, 2016


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