Disc-medllm: Bridging general large language models and real-world medical consultation
Z Bao, W Chen, S Xiao, K Ren, J Wu, C Zhong… - arXiv preprint arXiv …, 2023 - arxiv.org
We propose DISC-MedLLM, a comprehensive solution that leverages Large Language
Models (LLMs) to provide accurate and truthful medical response in end-to-end …
Models (LLMs) to provide accurate and truthful medical response in end-to-end …
DialogVED: A pre-trained latent variable encoder-decoder model for dialog response generation
Dialog response generation in open domain is an important research topic where the main
challenge is to generate relevant and diverse responses. In this paper, we propose a new …
challenge is to generate relevant and diverse responses. In this paper, we propose a new …
DISC-FinLLM: A Chinese financial large language model based on multiple experts fine-tuning
We propose Multiple Experts Fine-tuning Framework to build a financial large language
model (LLM), DISC-FinLLM. Our methodology improves general LLMs by endowing them …
model (LLM), DISC-FinLLM. Our methodology improves general LLMs by endowing them …
BERT-based response selection in dialogue systems using utterance attention mechanisms
Dialogue systems, one of the core research fields of natural language processing, attempt to
understand the utterances of a user and generate an appropriate response. Response …
understand the utterances of a user and generate an appropriate response. Response …
K-esconv: Knowledge injection for emotional support dialogue systems via prompt learning
Automatic psychological counseling requires mass of professional knowledge that can be
found in online counseling forums. Motivated by this, we propose K-ESConv, a novel prompt …
found in online counseling forums. Motivated by this, we propose K-ESConv, a novel prompt …
Pneg: Prompt-based negative response generation for dialogue response selection task
In retrieval-based dialogue systems, a response selection model acts as a ranker to select
the most appropriate response among several candidates. However, such selection models …
the most appropriate response among several candidates. However, such selection models …
Towards Efficient Coarse-grained Dialogue Response Selection
Coarse-grained response selection is a fundamental and essential subsystem for the widely
used retrieval-based chatbots, aiming to recall a coarse-grained candidate set from a large …
used retrieval-based chatbots, aiming to recall a coarse-grained candidate set from a large …
Exploring dense retrieval for dialogue response selection
Recent progress in deep learning has continuously improved the accuracy of dialogue
response selection. However, in real-world scenarios, the high computation cost forces …
response selection. However, in real-world scenarios, the high computation cost forces …
KNSE: A Knowledge-aware Natural Language Inference Framework for Dialogue Symptom Status Recognition
Symptom diagnosis in medical conversations aims to correctly extract both symptom entities
and their status from the doctor-patient dialogue. In this paper, we propose a novel …
and their status from the doctor-patient dialogue. In this paper, we propose a novel …
CauESC: A Causal Aware Model for Emotional Support Conversation
Emotional Support Conversation aims at reducing the seeker's emotional distress through
supportive response. Existing approaches have two limitations:(1) They ignore the emotion …
supportive response. Existing approaches have two limitations:(1) They ignore the emotion …