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09/18/2023
An Empirical Study of Scaling Instruct-Tuned Large Multimodal Models
Visual instruction tuning has recently shown encouraging progress with o...
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09/01/2023
Efficient RLHF: Reducing the Memory Usage of PPO
Reinforcement Learning with Human Feedback (RLHF) has revolutionized lan...
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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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05/16/2023
AR-Diffusion: Auto-Regressive Diffusion Model for Text Generation
Diffusion models have gained significant attention in the realm of image...
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05/01/2023
In-Context Learning Unlocked for Diffusion Models
We present Prompt Diffusion, a framework for enabling in-context learnin...
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04/23/2023
Enhancing Chain-of-Thoughts Prompting with Iterative Bootstrapping in Large Language Models
Large language models (LLMs) can achieve highly effective performance on...
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02/07/2023
What Matters In The Structured Pruning of Generative Language Models?
Auto-regressive large language models such as GPT-3 require enormous com...
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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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11/18/2022
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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10/13/2022
Explanations from Large Language Models Make Small Reasoners Better
Integrating free-text explanations to in-context learning of large langu...
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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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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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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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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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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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12/15/2021
Knowledge-Grounded Dialogue Generation with a Unified Knowledge Representation
Knowledge-grounded dialogue systems are challenging to build due to the ...
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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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06/17/2021
LoRA: Low-Rank Adaptation of Large Language Models
The dominant paradigm of natural language processing consists of large-s...
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05/31/2021
Memory-Efficient Differentiable Transformer Architecture Search
Differentiable architecture search (DARTS) is successfully applied in ma...
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05/10/2021
Poolingformer: Long Document Modeling with Pooling Attention
In this paper, we introduce a two-level attention schema, Poolingformer,...
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01/01/2021
Reader-Guided Passage Reranking for Open-Domain Question Answering
Current open-domain question answering (QA) systems often follow a Retri...
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01/01/2021
UnitedQA: A Hybrid Approach for Open Domain Question Answering
To date, most of recent work under the retrieval-reader framework for op...
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01/01/2021
NeurIPS 2020 EfficientQA Competition: Systems, Analyses and Lessons Learned
We review the EfficientQA competition from NeurIPS 2020. The competition...
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10/16/2020
CoDA: Contrast-enhanced and Diversity-promoting Data Augmentation for Natural Language Understanding
Data augmentation has been demonstrated as an effective strategy for imp...
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10/12/2020
Improving Self-supervised Pre-training via a Fully-Explored Masked Language Model
Masked Language Model (MLM) framework has been widely adopted for self-s...
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09/29/2020
A Simple but Tough-to-Beat Data Augmentation Approach for Natural Language Understanding and Generation
Adversarial training has been shown effective at endowing the learned re...
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09/17/2020
Generation-Augmented Retrieval for Open-domain Question Answering
Conventional sparse retrieval methods such as TF-IDF and BM25 are simple...
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05/16/2020
Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehension
In this paper, we study machine reading comprehension (MRC) on long text...
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05/16/2020
Recurrent Chunking Mechanisms for Long-Text Machine Reading Comprehensio
In this paper, we study machine reading comprehension (MRC) on long text...
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05/11/2020
MART: Memory-Augmented Recurrent Transformer for Coherent Video Paragraph Captioning
Generating multi-sentence descriptions for videos is one of the most cha...
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04/19/2019
A Hybrid Retrieval-Generation Neural Conversation Model
Intelligent personal assistant systems, with either text-based or voice-...
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04/03/2019
Unsupervised Deep Structured Semantic Models for Commonsense Reasoning
Commonsense reasoning is fundamental to natural language understanding. ...
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12/06/2018
StoryGAN: A Sequential Conditional GAN for Story Visualization
In this work we propose a new task called Story Visualization. Given a m...
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09/18/2018
Multi-Task Learning for Machine Reading Comprehension
We propose a multi-task learning framework to jointly train a Machine Re...
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02/12/2018
ReinforceWalk: Learning to Walk in Graph with Monte Carlo Tree Search
Learning to walk over a graph towards a target node for a given input qu...
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12/10/2017
Stochastic Answer Networks for Machine Reading Comprehension
We propose a simple yet robust stochastic answer network (SAN) that simu...
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11/16/2017
Language-Based Image Editing with Recurrent Attentive Models
We investigate the problem of Language-Based Image Editing (LBIE) in thi...
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11/16/2017
FusionNet: Fusing via Fully-Aware Attention with Application to Machine Comprehension
This paper introduces a new neural structure called FusionNet, which ext...
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11/14/2017
Towards Human-level Machine Reading Comprehension: Reasoning and Inference with Multiple Strategies
This paper presents a new MRC model that is capable of three key compreh...
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11/09/2017
An Empirical Analysis of Multiple-Turn Reasoning Strategies in Reading Comprehension Tasks
Reading comprehension (RC) is a challenging task that requires synthesis...
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11/14/2016
Traversing Knowledge Graph in Vector Space without Symbolic Space Guidance
Recent studies on knowledge base completion, the task of recovering miss...
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09/17/2016
ReasoNet: Learning to Stop Reading in Machine Comprehension
Teaching a computer to read and answer general questions pertaining to a...
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02/24/2015