Reasoning presents a significant and challenging issue for Large Languag...
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...
Information retrieval (IR) plays a crucial role in locating relevant
res...
Large Language Models (LLMs) have significantly advanced natural languag...
With the increasing development of e-commerce and online services,
perso...
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
...
In large-scale retrieval, the lexicon-weighting paradigm, learning weigh...
Retrieval models based on dense representations in semantic space have b...
Tag-aware recommendation is a task of predicting a personalized list of ...
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...
Current Knowledge-Grounded Dialogue Generation (KDG) models specialize i...
Generating natural and informative texts has been a long-standing proble...
This paper focuses on the Data Augmentation for low-resource Natural Lan...
Learning sentence embeddings in an unsupervised manner is fundamental in...
Recurrent recommender systems have been successful in capturing the temp...
Retrieve-based dialogue response selection aims to find a proper respons...
Responsing with image has been recognized as an important capability for...
In this paper, we present a pre-trained language model (PLM) based frame...
Though recent end-to-end neural models have shown promising progress on
...
We study the problem of coarse-grained response selection in retrieval-b...
Visual dialog is challenging since it needs to answer a series of cohere...
Recently, various neural models for multi-party conversation (MPC) have
...
Arguably, the visual perception of conversational agents to the physical...
Now, the pre-training technique is ubiquitous in natural language proces...
Organ transplantation is often the last resort for treating end-stage
il...
We study knowledge-grounded dialogue generation with pre-trained languag...
Generating responses following a desired style has great potentials to e...
While neural conversation models have shown great potentials towards
gen...
We consider grounding open domain dialogues with images. Existing work
a...
We study multi-turn response generation for open-domain dialogues. The
e...
Responding with knowledge has been recognized as an important capability...
This paper describes the systems submitted by the department of electron...
Automatic news comment generation is beneficial for real applications bu...
We study open domain response generation with limited message-response p...
We present open domain response generation with meta-words. A meta-word ...
We present a document-grounded matching network (DGMN) for response sele...
Understanding temporal dynamics has proved to be highly valuable for acc...
Most current state-of-the-art text-independent speaker verification syst...
The 20 Questions (Q20) game is a well known game which encourages deduct...
We consider matching with pre-trained contextualized word vectors for
mu...
We study open domain dialogue generation with dialogue acts designed to
...
We study response generation for open domain conversation in chatbots.
E...