Evaluating open-domain dialogue systems is challenging for reasons such ...
Augmenting large language models (LLMs) with external tools has emerged ...
The research field of Information Retrieval (IR) has evolved significant...
Answer selection in open-domain dialogues aims to select an accurate ans...
In open-domain question answering, due to the ambiguity of questions,
mu...
Explanations in conventional recommender systems have demonstrated benef...
Summarization quality evaluation is a non-trivial task in text summariza...
Learning reinforcement learning (RL)-based recommenders from historical
...
Recent work on knowledge graph completion (KGC) focused on learning
embe...
Recommender systems that learn from implicit feedback often use large vo...
Large Language Models (LLMs) have demonstrated a remarkable ability to
g...
Knowledge selection is the key in knowledge-grounded dialogues (KGD), wh...
Conventional document retrieval techniques are mainly based on the
index...
Sequential recommendations aim to capture users' preferences from their
...
Side information is being used extensively to improve the effectiveness ...
Conversational recommender systems (CRSs) often utilize external knowled...
Pre-trained language models (LMs) store knowledge in their parameters an...
Natural language understanding (NLU) models often rely on dataset biases...
Modern recommender systems are trained to predict users potential future...
Learned recommender systems may inadvertently leak information about the...
Modern recommender systems aim to improve user experience. As reinforcem...
Pre-trained language models (PLM) have demonstrated their effectiveness ...
Task-oriented dialogue systems (TDSs) are assessed mainly in an offline
...
Recently, recommender systems have achieved promising performances and b...
Medical dialogue systems (MDSs) aim to assist doctors and patients with ...
Electronic health record (EHR) coding is the task of assigning ICD codes...
One of the key challenges in Sequential Recommendation (SR) is how to ex...
Conversational information seeking (CIS) is playing an increasingly impo...
Contract element extraction (CEE) is the novel task of automatically
ide...
Medical dialogue generation aims to provide automatic and accurate respo...
Evaluation is crucial in the development process of task-oriented dialog...
There is increasing interest in developing personalized Task-oriented
Di...
Cross-domain sequential recommendation is the task of predict the next i...
Conversational interfaces are increasingly popular as a way of connectin...
Existing methods for Dialogue Response Generation (DRG) in Task-oriented...
Users prefer diverse recommendations over homogeneous ones. However, mos...
In this work we focus on multi-turn passage retrieval as a crucial compo...
In this paper, we address the problem of answering complex information n...
Unstructured Persona-oriented Dialogue Systems (UPDS) has been demonstra...
Dialogue response generation (DRG) is a critical component of task-orien...
Matrix factorization (MF) techniques have been shown to be effective for...
Sequential Recommendation (SR) has been attracting a growing attention f...
Sequential Recommendation (SR) has been attracting a growing attention f...
Sequential Recommendation (SRs) that capture users' dynamic intents by
m...
Background Based Conversations (BBCs) have been introduced to help
conve...
The task of fashion recommendation includes two main challenges: visual
...
Existing conversational systems tend to generate generic responses. Rece...
End-to-end Task-oriented Dialogue Systems (TDSs) have attracted a lot of...
Background Based Conversations (BBCs) have been developed to make dialog...
Sequence-to-Sequence (Seq2Seq) models have achieved encouraging performa...