b'Shafiq Joty'

research

∙ 09/17/2023

Embrace Divergence for Richer Insights: A Multi-document Summarization Benchmark and a Case Study on Summarizing Diverse Information from News Articles

Previous research in multi-document news summarization has typically con...

0 Kung-Hsiang Huang, et al. ∙

research

∙ 09/12/2023

RAP-Gen: Retrieval-Augmented Patch Generation with CodeT5 for Automatic Program Repair

Automatic program repair (APR) is crucial to reduce manual debugging eff...

0 Weishi Wang, et al. ∙

research

∙ 08/24/2023

Exploring the Integration Strategies of Retriever and Large Language Models

The integration of retrieved passages and large language models (LLMs), ...

0 Ye Liu, et al. ∙

research

∙ 08/06/2023

PromptSum: Parameter-Efficient Controllable Abstractive Summarization

Prompt tuning (PT), a parameter-efficient technique that only tunes the ...

0 Mathieu Ravaut, et al. ∙

research

∙ 06/20/2023

Democratizing LLMs for Low-Resource Languages by Leveraging their English Dominant Abilities with Linguistically-Diverse Prompts

Large language models (LLMs) are known to effectively perform tasks by s...

0 Xuan-Phi Nguyen, et al. ∙

research

∙ 06/01/2023

Did You Read the Instructions? Rethinking the Effectiveness of Task Definitions in Instruction Learning

Large language models (LLMs) have shown impressive performance in follow...

0 Fan Yin, et al. ∙

research

∙ 05/31/2023

Building Extractive Question Answering System to Support Human-AI Health Coaching Model for Sleep Domain

Non-communicable diseases (NCDs) are a leading cause of global deaths, n...

0 Iva Bojic, et al. ∙

research

∙ 05/30/2023

SWiPE: A Dataset for Document-Level Simplification of Wikipedia Pages

Text simplification research has mostly focused on sentence-level simpli...

0 Philippe Laban, et al. ∙

research

∙ 05/29/2023

A Systematic Study and Comprehensive Evaluation of ChatGPT on Benchmark Datasets

The development of large language models (LLMs) such as ChatGPT has brou...

0 Md Tahmid Rahman Laskar, et al. ∙

research

∙ 05/24/2023

Unlocking Temporal Question Answering for Large Language Models Using Code Execution

Large language models (LLMs) have made significant progress in natural l...

0 Xingxuan Li, et al. ∙

research

∙ 05/24/2023

UniChart: A Universal Vision-language Pretrained Model for Chart Comprehension and Reasoning

Charts are very popular for analyzing data, visualizing key insights and...

0 Ahmed Masry, et al. ∙

research

∙ 05/23/2023

LLMs as Factual Reasoners: Insights from Existing Benchmarks and Beyond

With the recent appearance of LLMs in practical settings, having methods...

0 Philippe Laban, et al. ∙

research

∙ 05/22/2023

Chain of Knowledge: A Framework for Grounding Large Language Models with Structured Knowledge Bases

We introduce Chain of Knowledge (CoK), a framework that augments large l...

0 Xingxuan Li, et al. ∙

research

∙ 05/11/2023

Randomized Smoothing with Masked Inference for Adversarially Robust Text Classifications

Large-scale pre-trained language models have shown outstanding performan...

11 Han Cheol Moon, et al. ∙

research

∙ 05/05/2023

Verify-and-Edit: A Knowledge-Enhanced Chain-of-Thought Framework

As large language models (LLMs) have become the norm in NLP, demonstrati...

17 Ruochen Zhao, et al. ∙

research

∙ 05/04/2023

Modeling What-to-ask and How-to-ask for Answer-unaware Conversational Question Generation

Conversational Question Generation (CQG) is a critical task for machines...

12 Xuan Long Do, et al. ∙

research

∙ 05/03/2023

Explaining Language Models' Predictions with High-Impact Concepts

The emergence of large-scale pretrained language models has posed unprec...

9 Ruochen Zhao, et al. ∙

research

∙ 04/03/2023

Efficiently Aligned Cross-Lingual Transfer Learning for Conversational Tasks using Prompt-Tuning

Cross-lingual transfer of language models trained on high-resource langu...

2 Lifu Tu, et al. ∙

research

∙ 04/02/2023

A Data-centric Framework for Improving Domain-specific Machine Reading Comprehension Datasets

Low-quality data can cause downstream problems in high-stakes applicatio...

5 Iva Bojic, et al. ∙

research

∙ 03/20/2023

Retrieving Multimodal Information for Augmented Generation: A Survey

In this survey, we review methods that retrieve multimodal knowledge to ...

17 Ruochen Zhao, et al. ∙

research

∙ 03/07/2023

Towards Interpretable and Efficient Automatic Reference-Based Summarization Evaluation

Interpretability and efficiency are two important considerations for the...

13 Yixin Liu, et al. ∙

research

∙ 03/06/2023

xCodeEval: A Large Scale Multilingual Multitask Benchmark for Code Understanding, Generation, Translation and Retrieval

The ability to solve problems is a hallmark of intelligence and has been...

0 Mohammad Abdullah Matin Khan, et al. ∙

research

∙ 02/16/2023

Learning to Initialize: Can Meta Learning Improve Cross-task Generalization in Prompt Tuning?

Prompt tuning (PT) which only tunes the embeddings of an additional sequ...

2 Chengwei Qin, et al. ∙

research

∙ 01/31/2023

Dynamic Scheduled Sampling with Imitation Loss for Neural Text Generation

State-of-the-art neural text generation models are typically trained to ...

6 Xiang Lin, et al. ∙

research

∙ 12/21/2022

SPT: Semi-Parametric Prompt Tuning for Multitask Prompted Learning

Pre-trained large language models can efficiently interpolate human-writ...

7 M Saiful Bari, et al. ∙

research

∙ 12/20/2022

Is GPT-3 a Psychopath? Evaluating Large Language Models from a Psychological Perspective

Are large language models (LLMs) like GPT-3 psychologically safe? In thi...

32 Xingxuan Li, et al. ∙

research

∙ 12/20/2022

Is GPT-3 a Good Data Annotator?

GPT-3 (Generative Pre-trained Transformer 3) is a large-scale autoregres...

34 Bosheng Ding, et al. ∙

research

∙ 12/19/2022

Unsupervised Summarization Re-ranking

With the rise of task-specific pre-training objectives, abstractive summ...

13 Mathieu Ravaut, et al. ∙

research

∙ 12/15/2022

Revisiting the Gold Standard: Grounding Summarization Evaluation with Robust Human Evaluation

Human evaluation is the foundation upon which the evaluation of both sum...

12 Yixin Liu, et al. ∙

research

∙ 11/30/2022

Learning Label Modular Prompts for Text Classification in the Wild

Machine learning models usually assume i.i.d data during training and te...

0 Hailin Chen, et al. ∙

research

∙ 11/29/2022

BotSIM: An End-to-End Bot Simulation Toolkit for Commercial Task-Oriented Dialog Systems

We introduce BotSIM, a modular, open-source Bot SIMulation environment w...

0 Guangsen Wang, et al. ∙

research

∙ 11/16/2022

Towards Robust Low-Resource Fine-Tuning with Multi-View Compressed Representations

Due to the huge amount of parameters, fine-tuning of pretrained language...

11 Linlin Liu, et al. ∙

research

∙ 11/08/2022

Alleviating Sparsity of Open Knowledge Graphs with Ternary Contrastive Learning

Sparsity of formal knowledge and roughness of non-ontological constructi...

0 Qian Li, et al. ∙

research

∙ 10/17/2022

Towards Summary Candidates Fusion

Sequence-to-sequence deep neural models fine-tuned for abstractive summa...

4 Mathieu Ravaut, et al. ∙

research

∙ 10/12/2022

OpenCQA: Open-ended Question Answering with Charts

Charts are very popular to analyze data and convey important insights. P...

17 Shankar Kantharaj, et al. ∙

research

∙ 09/23/2022

Improving Conversational Recommender System via Contextual and Time-Aware Modeling with Less Domain-Specific Knowledge

Conversational Recommender Systems (CRS) has become an emerging research...

2 Lingzhi Wang, et al. ∙

research

∙ 09/14/2022

CoHS-CQG: Context and History Selection for Conversational Question Generation

Conversational question generation (CQG) serves as a vital task for mach...

11 Xuan Long Do, et al. ∙

research

∙ 05/31/2022

Refining Low-Resource Unsupervised Translation by Language Disentanglement of Multilingual Model

Numerous recent work on unsupervised machine translation (UMT) implies t...

9 Xuan-Phi Nguyen, et al. ∙

research

∙ 03/25/2022

Data Selection Curriculum for Neural Machine Translation

Neural Machine Translation (NMT) models are typically trained on heterog...

10 Tasnim Mohiuddin, et al. ∙

research

∙ 03/19/2022

ChartQA: A Benchmark for Question Answering about Charts with Visual and Logical Reasoning

Charts are very popular for analyzing data. When exploring charts, peopl...

8 Ahmed Masry, et al. ∙

research

∙ 03/13/2022

SummaReranker: A Multi-Task Mixture-of-Experts Re-ranking Framework for Abstractive Summarization

Sequence-to-sequence neural networks have recently achieved great succes...

6 Mathieu Ravaut, et al. ∙

research

∙ 03/12/2022

Chart-to-Text: A Large-Scale Benchmark for Chart Summarization

Charts are commonly used for exploring data and communicating insights. ...

11 Shankar Kanthara, et al. ∙

research

∙ 03/04/2022

Continual Few-shot Relation Learning via Embedding Space Regularization and Data Augmentation

Existing continual relation learning (CRL) methods rely on plenty of lab...

1 Chengwei Qin, et al. ∙

research

∙ 11/22/2021

Knowledge Based Multilingual Language Model

Knowledge enriched language representation learning has shown promising ...

2 Linlin Liu, et al. ∙

research

∙ 10/16/2021

A Unified Speaker Adaptation Approach for ASR

Transformer models have been used in automatic speech recognition (ASR) ...

8 Yingzhu Zhao, et al. ∙

research

∙ 10/15/2021

Cascaded Fast and Slow Models for Efficient Semantic Code Search

The goal of natural language semantic code search is to retrieve a seman...

21 Akhilesh Deepak Gotmare, et al. ∙

research

∙ 10/14/2021

GlobalWoZ: Globalizing MultiWoZ to Develop Multilingual Task-Oriented Dialogue Systems

Much recent progress in task-oriented dialogue (ToD) systems has been dr...

8 Bosheng Ding, et al. ∙

research

∙ 10/14/2021

LFPT5: A Unified Framework for Lifelong Few-shot Language Learning Based on Prompt Tuning of T5

Existing approaches to lifelong language learning rely on plenty of labe...

10 Chengwei Qin, et al. ∙

research

∙ 10/14/2021

Rethinking Self-Supervision Objectives for Generalizable Coherence Modeling

Although large-scale pre-trained neural models have shown impressive per...

5 Prathyusha Jwalapuram, et al. ∙

research

∙ 09/02/2021

CodeT5: Identifier-aware Unified Pre-trained Encoder-Decoder Models for Code Understanding and Generation

Pre-trained models for Natural Languages (NL) like BERT and GPT have bee...

5 Yue Wang, et al. ∙

Shafiq Joty

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