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07/05/2023
Exploring Continual Learning for Code Generation Models
Large-scale code generation models such as Codex and CodeT5 have achieve...
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12/20/2022
ReCode: Robustness Evaluation of Code Generation Models
Code generation models have achieved impressive performance. However, th...
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12/20/2022
CoCoMIC: Code Completion By Jointly Modeling In-file and Cross-file Context
While pre-trained language models (LM) for code have achieved great succ...
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10/26/2022
Multi-lingual Evaluation of Code Generation Models
We present MBXP, an execution-based code completion benchmark in 10+ pro...
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10/03/2022
ContraGen: Effective Contrastive Learning For Causal Language Model
Despite exciting progress in large-scale language generation, the expres...
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09/28/2022
Improving Text-to-SQL Semantic Parsing with Fine-grained Query Understanding
Most recent research on Text-to-SQL semantic parsing relies on either pa...
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05/04/2022
Efficient Few-Shot Fine-Tuning for Opinion Summarization
Abstractive summarization models are typically pre-trained on large amou...
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03/21/2022
DQ-BART: Efficient Sequence-to-Sequence Model via Joint Distillation and Quantization
Large-scale pre-trained sequence-to-sequence models like BART and T5 ach...
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09/12/2021
Pairwise Supervised Contrastive Learning of Sentence Representations
Many recent successes in sentence representation learning have been achi...
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05/10/2021
Improving Factual Consistency of Abstractive Summarization via Question Answering
A commonly observed problem with the state-of-the art abstractive summar...
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04/17/2021
Transductive Learning for Abstractive News Summarization
Pre-trained language models have recently advanced abstractive summariza...
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03/24/2021
Supporting Clustering with Contrastive Learning
Unsupervised clustering aims at discovering the semantic categories of d...
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02/18/2021
Entity-level Factual Consistency of Abstractive Text Summarization
A key challenge for abstractive summarization is ensuring factual consis...
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11/26/2020
Answering Ambiguous Questions through Generative Evidence Fusion and Round-Trip Prediction
In open-domain question answering, questions are highly likely to be amb...
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10/12/2020
End-to-End Synthetic Data Generation for Domain Adaptation of Question Answering Systems
We propose an end-to-end approach for synthetic QA data generation. Our ...
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10/06/2020
Beyond [CLS] through Ranking by Generation
Generative models for Information Retrieval, where ranking of documents ...
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09/22/2020
Embedding-based Zero-shot Retrieval through Query Generation
Passage retrieval addresses the problem of locating relevant passages, u...
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04/24/2020
Template-Based Question Generation from Retrieved Sentences for Improved Unsupervised Question Answering
Question Answering (QA) is in increasing demand as the amount of informa...
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11/25/2019
Who did They Respond to? Conversation Structure Modeling using Masked Hierarchical Transformer
Conversation structure is useful for both understanding the nature of co...
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10/17/2019
Universal Text Representation from BERT: An Empirical Study
We present a systematic investigation of layer-wise BERT activations for...
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09/17/2019
Multi Sense Embeddings from Topic Models
Distributed word embeddings have yielded state-of-the-art performance in...
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08/22/2019
Multi-passage BERT: A Globally Normalized BERT Model for Open-domain Question Answering
BERT model has been successfully applied to open-domain QA tasks. Howeve...
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07/24/2019
Topic Modeling with Wasserstein Autoencoders
We propose a novel neural topic model in the Wasserstein autoencoders (W...
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05/15/2019
Passage Ranking with Weak Supervision
In this paper, we propose a weak supervision framework for neural rankin...
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05/15/2019
Passage Ranking with Weak Supervsion
In this paper, we propose a weak supervision framework for neural rankin...
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03/20/2019
OCGAN: One-class Novelty Detection Using GANs with Constrained Latent Representations
We present a novel model called OCGAN for the classical problem of one-c...
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09/07/2018
Coherence-Aware Neural Topic Modeling
Topic models are evaluated based on their ability to describe documents ...
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08/01/2017
SenGen: Sentence Generating Neural Variational Topic Model
We present a new topic model that generates documents by sampling a topi...
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11/14/2016
Classify or Select: Neural Architectures for Extractive Document Summarization
We present two novel and contrasting Recurrent Neural Network (RNN) base...
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11/14/2016
SummaRuNNer: A Recurrent Neural Network based Sequence Model for Extractive Summarization of Documents
We present SummaRuNNer, a Recurrent Neural Network (RNN) based sequence ...
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03/26/2016
Pointing the Unknown Words
The problem of rare and unknown words is an important issue that can pot...
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02/19/2016
