research
∙
09/12/2023
Re-Reading Improves Reasoning in Language Models
Reasoning presents a significant and challenging issue for Large Languag...
share
research
∙
08/26/2023
ZC3: Zero-Shot Cross-Language Code Clone Detection
Developers introduce code clones to improve programming productivity. Ma...
research
∙
08/18/2023
WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct
Large language models (LLMs), such as GPT-4, have shown remarkable perfo...
research
∙
07/28/2023
Investigating the Learning Behaviour of In-context Learning: A Comparison with Supervised Learning
Large language models (LLMs) have shown remarkable capacity for in-conte...
research
∙
06/14/2023
WizardCoder: Empowering Code Large Language Models with Evol-Instruct
Code Large Language Models (Code LLMs), such as StarCoder, have demonstr...
research
∙
06/01/2023
Improving the Robustness of Summarization Systems with Dual Augmentation
A robust summarization system should be able to capture the gist of the ...
research
∙
05/26/2023
UMSE: Unified Multi-scenario Summarization Evaluation
Summarization quality evaluation is a non-trivial task in text summariza...
research
∙
05/22/2023
MADNet: Maximizing Addressee Deduction Expectation for Multi-Party Conversation Generation
Modeling multi-party conversations (MPCs) with graph neural networks has...
research
∙
05/12/2023
Knowledge Refinement via Interaction Between Search Engines and Large Language Models
Information retrieval (IR) plays a crucial role in locating relevant res...
research
∙
05/08/2023
Augmented Large Language Models with Parametric Knowledge Guiding
Large Language Models (LLMs) have significantly advanced natural languag...
research
∙
04/27/2023
Large Language Models are Strong Zero-Shot Retriever
In this work, we propose a simple method that applies a large language m...
research
∙
04/24/2023
WizardLM: Empowering Large Language Models to Follow Complex Instructions
Training large language models (LLM) with open-domain instruction follow...
research
∙
02/06/2023
LexLIP: Lexicon-Bottlenecked Language-Image Pre-Training for Large-Scale Image-Text Retrieval
Image-text retrieval (ITR) is a task to retrieve the relevant images/tex...
research
∙
12/20/2022
Fine-Grained Distillation for Long Document Retrieval
Long document retrieval aims to fetch query-relevant documents from a la...
research
∙
12/20/2022
Adam: Dense Retrieval Distillation with Adaptive Dark Examples
To improve the performance of the dual-encoder retriever, one effective ...
research
∙
11/10/2022
MMDialog: A Large-scale Multi-turn Dialogue Dataset Towards Multi-modal Open-domain Conversation
Responding with multi-modal content has been recognized as an essential ...
research
∙
10/22/2022
Collaborative Reasoning on Multi-Modal Semantic Graphs for Video-Grounded Dialogue Generation
We study video-grounded dialogue generation, where a response is generat...
research
∙
08/31/2022
LexMAE: Lexicon-Bottlenecked Pretraining for Large-Scale Retrieval
In large-scale retrieval, the lexicon-weighting paradigm, learning weigh...
research
∙
08/29/2022
LED: Lexicon-Enlightened Dense Retriever for Large-Scale Retrieval
Retrieval models based on dense representations in semantic space have b...
research
∙
06/21/2022
KnowDA: All-in-One Knowledge Mixture Model for Data Augmentation in Few-Shot NLP
This paper focuses on text data augmentation for few-shot NLP tasks. The...
research
∙
06/16/2022
Towards Robust Ranker for Text Retrieval
A ranker plays an indispensable role in the de facto 'retrieval rera...
research
∙
05/23/2022
UnifieR: A Unified Retriever for Large-Scale Retrieval
Large-scale retrieval is to recall relevant documents from a huge collec...
research
∙
03/16/2022
TegTok: Augmenting Text Generation via Task-specific and Open-world Knowledge
Generating natural and informative texts has been a long-standing proble...
research
∙
03/16/2022
HeterMPC: A Heterogeneous Graph Neural Network for Response Generation in Multi-Party Conversations
Recently, various response generation models for two-party conversations...
research
∙
02/25/2022
PromDA: Prompt-based Data Augmentation for Low-Resource NLU Tasks
This paper focuses on the Data Augmentation for low-resource Natural Lan...
research
∙
01/28/2022
PCL: Peer-Contrastive Learning with Diverse Augmentations for Unsupervised Sentence Embeddings
Learning sentence embeddings in an unsupervised manner is fundamental in...
research
∙
10/01/2021
Building an Efficient and Effective Retrieval-based Dialogue System via Mutual Learning
Establishing retrieval-based dialogue systems that can select appropriat...
research
∙
06/03/2021
MPC-BERT: A Pre-Trained Language Model for Multi-Party Conversation Understanding
Recently, various neural models for multi-party conversation (MPC) have ...
research
∙
05/27/2021
Maria: A Visual Experience Powered Conversational Agent
Arguably, the visual perception of conversational agents to the physical...
research
∙
05/07/2021
A Benchmarking on Cloud based Speech-To-Text Services for French Speech and Background Noise Effect
This study presents a large scale benchmarking on cloud based Speech-To-...
research
∙
08/29/2020
Zero-Resource Knowledge-Grounded Dialogue Generation
While neural conversation models have shown great potentials towards gen...
research
∙
04/30/2020
EnsembleGAN: Adversarial Learning for Retrieval-Generation Ensemble Model on Short-Text Conversation
Generating qualitative responses has always been a challenge for human-c...
research
∙
02/24/2020
Low-Resource Knowledge-Grounded Dialogue Generation
Responding with knowledge has been recognized as an important capability...
research
∙
06/18/2019
Mimicking Human Process: Text Representation via Latent Semantic Clustering for Classification
Considering that words with different characteristic in the text have di...
research
∙
06/14/2019
Neural Response Generation with Meta-Words
We present open domain response generation with meta-words. A meta-word ...
research
∙
06/11/2019
Learning a Matching Model with Co-teaching for Multi-turn Response Selection in Retrieval-based Dialogue Systems
We study learning of a matching model for response selection in retrieva...
research
∙
06/11/2019
A Document-grounded Matching Network for Response Selection in Retrieval-based Chatbots
We present a document-grounded matching network (DGMN) for response sele...
research
∙
09/27/2018
Iterative Document Representation Learning Towards Summarization with Polishing
In this paper, we introduce Iterative Text Summarization (ITS), an itera...
research
∙
08/23/2018
Playing 20 Question Game with Policy-Based Reinforcement Learning
The 20 Questions (Q20) game is a well known game which encourages deduct...
research
∙
08/22/2018
Improving Matching Models with Contextualized Word Representations for Multi-turn Response Selection in Retrieval-based Chatbots
We consider matching with pre-trained contextualized word vectors for mu...
research
∙
01/11/2017
