research
∙
08/10/2023
Few-Shot Data-to-Text Generation via Unified Representation and Multi-Source Learning
We present a novel approach for structured data-to-text generation that ...
share
research
∙
07/11/2023
Self-consistency for open-ended generations
In this paper, we present a novel approach for improving the quality and...
research
∙
07/05/2023
Exploring Continual Learning for Code Generation Models
Large-scale code generation models such as Codex and CodeT5 have achieve...
research
∙
06/05/2023
A Static Evaluation of Code Completion by Large Language Models
Large language models trained on code have shown great potential to incr...
research
∙
05/30/2023
Generate then Select: Open-ended Visual Question Answering Guided by World Knowledge
The open-ended Visual Question Answering (VQA) task requires AI models t...
research
∙
05/27/2023
Benchmarking Diverse-Modal Entity Linking with Generative Models
Entities can be expressed in diverse formats, such as texts, images, or ...
research
∙
05/25/2023
UNITE: A Unified Benchmark for Text-to-SQL Evaluation
A practical text-to-SQL system should generalize well on a wide variety ...
research
∙
03/09/2023
Greener yet Powerful: Taming Large Code Generation Models with Quantization
ML-powered code generation aims to assist developers to write code in a ...
research
∙
02/28/2023
Linear Spaces of Meanings: the Compositional Language of VLMs
We investigate compositional structures in vector data embeddings from p...
research
∙
02/13/2023
STREET: A Multi-Task Structured Reasoning and Explanation Benchmark
We introduce STREET, a unified multi-task and multi-domain natural langu...
research
∙
01/21/2023
Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustness
Neural text-to-SQL models have achieved remarkable performance in transl...
research
∙
12/20/2022
ReCode: Robustness Evaluation of Code Generation Models
Code generation models have achieved impressive performance. However, th...
research
∙
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...
research
∙
12/17/2022
Importance of Synthesizing High-quality Data for Text-to-SQL Parsing
Recently, there has been increasing interest in synthesizing data to imp...
research
∙
10/26/2022
Multi-lingual Evaluation of Code Generation Models
We present MBXP, an execution-based code completion benchmark in 10+ pro...
research
∙
10/03/2022
ContraGen: Effective Contrastive Learning For Causal Language Model
Despite exciting progress in large-scale language generation, the expres...
research
∙
09/30/2022
DecAF: Joint Decoding of Answers and Logical Forms for Question Answering over Knowledge Bases
Question answering over knowledge bases (KBs) aims to answer natural lan...
research
∙
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...
research
∙
06/10/2022
REKnow: Enhanced Knowledge for Joint Entity and Relation Extraction
Relation extraction is an important but challenging task that aims to ex...
research
∙
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...
research
∙
10/20/2021
Contrastive Document Representation Learning with Graph Attention Networks
Recent progress in pretrained Transformer-based language models has show...
research
∙
10/12/2021
Attention-guided Generative Models for Extractive Question Answering
We propose a novel method for applying Transformer models to extractive ...
research
∙
09/27/2021
Multiplicative Position-aware Transformer Models for Language Understanding
Transformer models, which leverage architectural improvements like self-...
research
∙
09/12/2021
Pairwise Supervised Contrastive Learning of Sentence Representations
Many recent successes in sentence representation learning have been achi...
research
∙
08/05/2021
Dual Reader-Parser on Hybrid Textual and Tabular Evidence for Open Domain Question Answering
The current state-of-the-art generative models for open-domain question ...
research
∙
05/10/2021
Improving Factual Consistency of Abstractive Summarization via Question Answering
A commonly observed problem with the state-of-the art abstractive summar...
research
∙
04/18/2021
Generative Context Pair Selection for Multi-hop Question Answering
Compositional reasoning tasks like multi-hop question answering, require...
research
∙
03/24/2021
Supporting Clustering with Contrastive Learning
Unsupervised clustering aims at discovering the semantic categories of d...
research
∙
02/18/2021
Entity-level Factual Consistency of Abstractive Text Summarization
A key challenge for abstractive summarization is ensuring factual consis...
research
∙
01/14/2021
Structured Prediction as Translation between Augmented Natural Languages
We propose a new framework, Translation between Augmented Natural Langua...
research
∙
12/18/2020
Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Training
Most recently, there has been significant interest in learning contextua...
research
∙
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...
research
∙
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 ...
research
∙
10/06/2020
Beyond [CLS] through Ranking by Generation
Generative models for Information Retrieval, where ranking of documents ...
research
∙
09/28/2020
Improve Transformer Models with Better Relative Position Embeddings
Transformer architectures rely on explicit position encodings in order t...
research
∙
09/22/2020
Embedding-based Zero-shot Retrieval through Query Generation
Passage retrieval addresses the problem of locating relevant passages, u...
research
∙
09/15/2020
Augmented Natural Language for Generative Sequence Labeling
We propose a generative framework for joint sequence labeling and senten...
research
∙
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...
research
∙
03/16/2020
TRANS-BLSTM: Transformer with Bidirectional LSTM for Language Understanding
Bidirectional Encoder Representations from Transformers (BERT) has recen...
research
∙
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...
research
∙
10/17/2019
Universal Text Representation from BERT: An Empirical Study
We present a systematic investigation of layer-wise BERT activations for...
research
∙
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...
research
∙
07/24/2019
Topic Modeling with Wasserstein Autoencoders
We propose a novel neural topic model in the Wasserstein autoencoders (W...
research
∙
05/15/2019
Passage Ranking with Weak Supervision
In this paper, we propose a weak supervision framework for neural rankin...
research
∙
05/15/2019
Passage Ranking with Weak Supervsion
In this paper, we propose a weak supervision framework for neural rankin...
research
∙
04/08/2019
WeNet: Weighted Networks for Recurrent Network Architecture Search
In recent years, there has been increasing demand for automatic architec...
research
∙
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...
research
∙
09/07/2018
Coherence-Aware Neural Topic Modeling
Topic models are evaluated based on their ability to describe documents ...
research
∙
05/13/2018
Neural Coreference Resolution with Deep Biaffine Attention by Joint Mention Detection and Mention Clustering
Coreference resolution aims to identify in a text all mentions that refe...
research
∙
10/07/2017
