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09/02/2023
Bias and Fairness in Large Language Models: A Survey
Rapid advancements of large language models (LLMs) have enabled the proc...
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08/22/2023
Knowledge Graph Prompting for Multi-Document Question Answering
The 'pre-train, prompt, predict' paradigm of large language models (LLMs...
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07/23/2023
Learning Navigational Visual Representations with Semantic Map Supervision
Being able to perceive the semantics and the spatial structure of the en...
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06/29/2023
LLaVAR: Enhanced Visual Instruction Tuning for Text-Rich Image Understanding
Instruction tuning unlocks the superior capability of Large Language Mod...
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05/31/2023
Label-Retrieval-Augmented Diffusion Models for Learning from Noisy Labels
Learning from noisy labels is an important and long-standing problem in ...
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05/23/2023
Enhancing Detail Preservation for Customized Text-to-Image Generation: A Regularization-Free Approach
Recent text-to-image generation models have demonstrated impressive capa...
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05/20/2023
Few-Shot Dialogue Summarization via Skeleton-Assisted Prompt Transfer
In real-world scenarios, labeled samples for dialogue summarization are ...
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05/09/2023
Towards Building the Federated GPT: Federated Instruction Tuning
While “instruction-tuned" generative large language models (LLMs) have d...
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10/19/2022
Robustness of Demonstration-based Learning Under Limited Data Scenario
Demonstration-based learning has shown great potential in stimulating pr...
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07/18/2022
STT: Soft Template Tuning for Few-Shot Adaptation
Prompt tuning has been an extremely effective tool to adapt a pre-traine...
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05/26/2022
Federated Non-negative Matrix Factorization for Short Texts Topic Modeling with Mutual Information
Non-negative matrix factorization (NMF) based topic modeling is widely u...
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11/27/2021
LAFITE: Towards Language-Free Training for Text-to-Image Generation
One of the major challenges in training text-to-image generation models ...
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09/09/2021
Graphine: A Dataset for Graph-aware Terminology Definition Generation
Precisely defining the terminology is the first step in scientific commu...
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03/17/2021
Improving Zero-shot Voice Style Transfer via Disentangled Representation Learning
Voice style transfer, also called voice conversion, seeks to modify one ...
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01/02/2021
SDA: Improving Text Generation with Self Data Augmentation
Data augmentation has been widely used to improve deep neural networks i...
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10/12/2020
Improving Text Generation with Student-Forcing Optimal Transport
Neural language models are often trained with maximum likelihood estimat...
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09/20/2020
Repulsive Attention: Rethinking Multi-head Attention as Bayesian Inference
The neural attention mechanism plays an important role in many natural l...
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09/15/2020
Unsupervised Abstractive Dialogue Summarization for Tete-a-Tetes
High-quality dialogue-summary paired data is expensive to produce and do...
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07/09/2020
Influence Diagram Bandits: Variational Thompson Sampling for Structured Bandit Problems
We propose a novel framework for structured bandits, which we call an in...
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05/24/2020
When does MAML Work the Best? An Empirical Study on Model-Agnostic Meta-Learning in NLP Applications
Model-Agnostic Meta-Learning (MAML), a model-agnostic meta-learning meth...
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05/04/2020
Reward Constrained Interactive Recommendation with Natural Language Feedback
Text-based interactive recommendation provides richer user feedback and ...
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05/04/2020
Improving Adversarial Text Generation by Modeling the Distant Future
Auto-regressive text generation models usually focus on local fluency, a...
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03/14/2020
Security Analysis of EOSIO Smart Contracts
The EOSIO blockchain, one of the representative Delegated Proof-of-Stake...
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02/21/2020
GenDICE: Generalized Offline Estimation of Stationary Values
An important problem that arises in reinforcement learning and Monte Car...
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01/20/2020
Nested-Wasserstein Self-Imitation Learning for Sequence Generation
Reinforcement learning (RL) has been widely studied for improving sequen...
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12/21/2019
Learning Diverse Stochastic Human-Action Generators by Learning Smooth Latent Transitions
Human-motion generation is a long-standing challenging task due to the r...
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10/21/2019
Collaborative Filtering with A Synthetic Feedback Loop
We propose a novel learning framework for recommendation systems, assist...
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09/30/2019
Improving Textual Network Learning with Variational Homophilic Embeddings
The performance of many network learning applications crucially hinges o...
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06/07/2019
Figure Captioning with Reasoning and Sequence-Level Training
Figures, such as bar charts, pie charts, and line plots, are widely used...
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03/17/2019
Topic-Guided Variational Autoencoders for Text Generation
We propose a topic-guided variational autoencoder (TGVAE) model for text...
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02/19/2019
Scalable Thompson Sampling via Optimal Transport
Thompson sampling (TS) is a class of algorithms for sequential decision-...
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01/18/2019
Improving Sequence-to-Sequence Learning via Optimal Transport
Sequence-to-sequence models are commonly trained via maximum likelihood ...
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11/02/2018
Sequence Generation with Guider Network
Sequence generation with reinforcement learning (RL) has received signif...
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09/05/2018
Stochastic Particle-Optimization Sampling and the Non-Asymptotic Convergence Theory
Particle-optimization sampling (POS) is a recently developed technique t...
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08/09/2018
Policy Optimization as Wasserstein Gradient Flows
Policy optimization is a core component of reinforcement learning (RL), ...
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07/04/2018
Accelerated First-order Methods on the Wasserstein Space for Bayesian Inference
We consider doing Bayesian inference by minimizing the KL divergence on ...
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05/29/2018
A Unified Particle-Optimization Framework for Scalable Bayesian Sampling
There has been recent interest in developing scalable Bayesian sampling ...
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12/30/2017
Learning Structural Weight Uncertainty for Sequential Decision-Making
Learning probability distributions on the weights of neural networks (NN...
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11/29/2017
