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09/06/2023
Deep Reinforcement Learning from Hierarchical Weak Preference Feedback
Reward design is a fundamental, yet challenging aspect of practical rein...
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06/20/2023
LoSparse: Structured Compression of Large Language Models based on Low-Rank and Sparse Approximation
Transformer models have achieved remarkable results in various natural l...
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05/24/2023
Enhancing Retrieval-Augmented Large Language Models with Iterative Retrieval-Generation Synergy
Large language models are powerful text processors and reasoners, but ar...
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05/24/2023
GRILL: Grounded Vision-language Pre-training via Aligning Text and Image Regions
Generalization to unseen tasks is an important ability for few-shot lear...
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05/23/2023
Skill-Based Few-Shot Selection for In-Context Learning
In-Context learning is the paradigm that adapts large language models to...
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05/16/2023
AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation
Diffusion models have gained significant attention in the realm of image...
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05/08/2023
Code Execution with Pre-trained Language Models
Code execution is a fundamental aspect of programming language semantics...
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05/01/2023
In-Context Learning Unlocked for Diffusion Models
We present Prompt Diffusion, a framework for enabling in-context learnin...
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04/25/2023
Patch Diffusion: Faster and More Data-Efficient Training of Diffusion Models
Diffusion models are powerful, but they require a lot of time and data t...
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04/13/2023
AGIEval: A Human-Centric Benchmark for Evaluating Foundation Models
Evaluating the general abilities of foundation models to tackle human-le...
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03/29/2023
AnnoLLM: Making Large Language Models to Be Better Crowdsourced Annotators
Many natural language processing (NLP) tasks rely on labeled data to tra...
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03/22/2023
RepoCoder: Repository-Level Code Completion Through Iterative Retrieval and Generation
The task of repository-level code completion is to continue writing the ...
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03/18/2023
Adaptive Budget Allocation for Parameter-Efficient Fine-Tuning
Fine-tuning large pre-trained language models on downstream tasks has be...
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03/13/2023
Meet in the Middle: A New Pre-training Paradigm
Most language models (LMs) are trained and applied in an autoregressive ...
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02/24/2023
Check Your Facts and Try Again: Improving Large Language Models with External Knowledge and Automated Feedback
Large language models (LLMs), such as ChatGPT, are able to generate huma...
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02/01/2023
Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models
Large language models can perform various reasoning tasks by using chain...
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12/22/2022
GENIE: Large Scale Pre-training for Text Generation with Diffusion Model
In this paper, we propose a large-scale language pre-training for text G...
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12/20/2022
Generation-Augmented Query Expansion For Code Retrieval
Pre-trained language models have achieved promising success in code retr...
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11/22/2022
HyperTuning: Toward Adapting Large Language Models without Back-propagation
Fine-tuning large language models for different tasks can be costly and ...
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11/18/2022
GENIUS: Sketch-based Language Model Pre-training via Extreme and Selective Masking for Text Generation and Augmentation
We introduce GENIUS: a conditional text generation model using sketches ...
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10/21/2022
SimANS: Simple Ambiguous Negatives Sampling for Dense Text Retrieval
Sampling proper negatives from a large document pool is vital to effecti...
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10/18/2022
Soft-Labeled Contrastive Pre-training for Function-level Code Representation
Code contrastive pre-training has recently achieved significant progress...
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10/04/2022
Less is More: Task-aware Layer-wise Distillation for Language Model Compression
Layer-wise distillation is a powerful tool to compress large models (i.e...
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07/21/2022
CodeT: Code Generation with Generated Tests
The task of generating code solutions for a given programming problem ca...
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07/08/2022
OmniTab: Pretraining with Natural and Synthetic Data for Few-shot Table-based Question Answering
The information in tables can be an important complement to text, making...
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06/28/2022
Joint Generator-Ranker Learning for Natural Language Generation
Due to exposure bias, most existing natural language generation (NLG) mo...
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06/25/2022
PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance
Large Transformer-based models have exhibited superior performance in va...
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06/14/2022
CERT: Continual Pre-Training on Sketches for Library-Oriented Code Generation
Code generation is a longstanding challenge, aiming to generate a code s...
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06/06/2022
On the Advance of Making Language Models Better Reasoners
Large language models such as GPT-3 and PaLM have shown remarkable perfo...
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06/05/2022
Diffusion-GAN: Training GANs with Diffusion
For stable training of generative adversarial networks (GANs), injecting...
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05/23/2022
A Self-Paced Mixed Distillation Method for Non-Autoregressive Generation
Non-Autoregressive generation is a sequence generation paradigm, which r...
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05/10/2022
ALLSH: Active Learning Guided by Local Sensitivity and Hardness
Active learning, which effectively collects informative unlabeled data f...
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04/27/2022
DialogVED: A Pre-trained Latent Variable Encoder-Decoder Model for Dialog Response Generation
Dialog response generation in open domain is an important research topic...
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04/15/2022
MoEBERT: from BERT to Mixture-of-Experts via Importance-Guided Adaptation
Pre-trained language models have demonstrated superior performance in va...
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04/13/2022
CAMERO: Consistency Regularized Ensemble of Perturbed Language Models with Weight Sharing
Model ensemble is a popular approach to produce a low-variance and well-...
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03/07/2022
Tensor Programs V: Tuning Large Neural Networks via Zero-Shot Hyperparameter Transfer
Hyperparameter (HP) tuning in deep learning is an expensive process, pro...
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03/07/2022
Input-Tuning: Adapting Unfamiliar Inputs to Frozen Pretrained Models
Recently the prompt-tuning paradigm has attracted significant attention....
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02/27/2022
Controllable Natural Language Generation with Contrastive Prefixes
To guide the generation of large pretrained language models (LM), previo...
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02/19/2022
Truncated Diffusion Probabilistic Models
Employing a forward Markov diffusion chain to gradually map the data to ...
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02/14/2022
Mixing and Shifting: Exploiting Global and Local Dependencies in Vision MLPs
Token-mixing multi-layer perceptron (MLP) models have shown competitive ...
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02/06/2022
No Parameters Left Behind: Sensitivity Guided Adaptive Learning Rate for Training Large Transformer Models
Recent research has shown the existence of significant redundancy in lar...
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01/27/2022
Reasoning Like Program Executors
Reasoning over natural language is a long-standing goal for the research...
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01/26/2022
CodeRetriever: Unimodal and Bimodal Contrastive Learning
In this paper, we propose the CodeRetriever model, which combines the un...
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12/06/2021
Contextual Bandit Applications in Customer Support Bot
Virtual support agents have grown in popularity as a way for businesses ...
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11/18/2021
DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing
This paper presents a new pre-trained language model, DeBERTaV3, which i...
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10/30/2021
DSEE: Dually Sparsity-embedded Efficient Tuning of Pre-trained Language Models
Gigantic pre-trained models have become central to natural language proc...
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10/16/2021
A Good Prompt Is Worth Millions of Parameters? Low-resource Prompt-based Learning for Vision-Language Models
Large pretrained vision-language (VL) models can learn a new task with a...
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10/07/2021
Adversarial Retriever-Ranker for dense text retrieval
Current dense text retrieval models face two typical challenges. First, ...
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09/26/2021
XLM-K: Improving Cross-Lingual Language Model Pre-Training with Multilingual Knowledge
Cross-lingual pre-training has achieved great successes using monolingua...
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09/15/2021
