Search Results for author:
Found 9 papers, 4 papers with code
Not Just Classification: Recognizing Implicit Discourse Relation on Joint Modeling of Classification and Generation
Therefore, we first view IDRR as a generation task and further propose a method joint modeling of the classification and generation.
A Distance-Aware Multi-Task Framework for Conversational Discourse Parsing
Conversational discourse parsing aims to construct an implicit utterance dependency tree to reflect the turn-taking in a multi-party conversation.
Quantifying Self-diagnostic Atomic Knowledge in Chinese Medical Foundation Model: A Computational Analysis
Recent studies primarily focused on the quality of FMs evaluated by GPT-4 or their ability to pass medical exams, no studies have quantified the extent of self-diagnostic atomic knowledge stored in FMs' memory, which is the basis of foundation models to provide factual and reliable suggestions.
PlatoLM: Teaching LLMs via a Socratic Questioning User Simulator
The unparalleled performance of closed-sourced ChatGPT has sparked efforts towards its democratization, with notable strides made by leveraging real user and ChatGPT conversations, as evidenced by Vicuna.
GrammarGPT: Exploring Open-Source LLMs for Native Chinese Grammatical Error Correction with Supervised Fine-Tuning
Although model parameters are 20x larger than the SOTA baseline, the required amount of data for instruction tuning is 1200x smaller, illustrating the potential of open-source LLMs on native CGEC.
Multi-Granularity Prompts for Topic Shift Detection in Dialogue
The goal of dialogue topic shift detection is to identify whether the current topic in a conversation has changed or needs to change.
Uncovering the Potential of ChatGPT for Discourse Analysis in Dialogue: An Empirical Study
In this paper, we aim to systematically inspect ChatGPT's performance in two discourse analysis tasks: topic segmentation and discourse parsing, focusing on its deep semantic understanding of linear and hierarchical discourse structures underlying dialogue.
Topic Shift Detection in Chinese Dialogues: Corpus and Benchmark
And then we focus on the response-unknown task and propose a teacher-student framework based on hierarchical contrastive learning to predict the topic shift without the response.
