Reasoning presents a significant and challenging issue for Large Languag...
Developers introduce code clones to improve programming productivity. Ma...
Large language models (LLMs), such as GPT-4, have shown remarkable
perfo...
Large language models (LLMs) have shown remarkable capacity for in-conte...
Code Large Language Models (Code LLMs), such as StarCoder, have demonstr...
A robust summarization system should be able to capture the gist of the
...
Summarization quality evaluation is a non-trivial task in text summariza...
Modeling multi-party conversations (MPCs) with graph neural networks has...
Information retrieval (IR) plays a crucial role in locating relevant
res...
Large Language Models (LLMs) have significantly advanced natural languag...
In this work, we propose a simple method that applies a large language m...
Training large language models (LLM) with open-domain instruction follow...
Image-text retrieval (ITR) is a task to retrieve the relevant images/tex...
Long document retrieval aims to fetch query-relevant documents from a
la...
To improve the performance of the dual-encoder retriever, one effective
...
Responding with multi-modal content has been recognized as an essential
...
We study video-grounded dialogue generation, where a response is generat...
In large-scale retrieval, the lexicon-weighting paradigm, learning weigh...
Retrieval models based on dense representations in semantic space have b...
This paper focuses on text data augmentation for few-shot NLP tasks. The...
A ranker plays an indispensable role in the de facto 'retrieval rera...
Large-scale retrieval is to recall relevant documents from a huge collec...
Generating natural and informative texts has been a long-standing proble...
Recently, various response generation models for two-party conversations...
This paper focuses on the Data Augmentation for low-resource Natural Lan...
Learning sentence embeddings in an unsupervised manner is fundamental in...
Establishing retrieval-based dialogue systems that can select appropriat...
Recently, various neural models for multi-party conversation (MPC) have
...
Arguably, the visual perception of conversational agents to the physical...
This study presents a large scale benchmarking on cloud based Speech-To-...
While neural conversation models have shown great potentials towards
gen...
Generating qualitative responses has always been a challenge for
human-c...
Responding with knowledge has been recognized as an important capability...
Considering that words with different characteristic in the text have
di...
We present open domain response generation with meta-words. A meta-word ...
We study learning of a matching model for response selection in
retrieva...
We present a document-grounded matching network (DGMN) for response sele...
In this paper, we introduce Iterative Text Summarization (ITS), an
itera...
The 20 Questions (Q20) game is a well known game which encourages deduct...
We consider matching with pre-trained contextualized word vectors for
mu...
Open-domain human-computer conversation has been attracting increasing
a...