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Feijun Jiang

6 accepted papers

2025

ADC: Enhancing Function Calling Via Adversarial Datasets and Code Line-Level Feedback

ICASSP 2025accepted

Large Language Models (LLMs) have made significant strides in Natural Language Processing and coding, yet they struggle with robustness and accuracy in complex function calls. To tackle these challenges, this paper introduces ADC, an innovative approach that enhances LLMs’ ability to follow function…

Cited by 0SourceScholar
2024

CO3: Low-resource Contrastive Co-training for Generative Conversational Query Rewrite

COLING 2024main

Generative query rewrite generates reconstructed query rewrites using the conversation history while rely heavily on gold rewrite pairs that are expensive to obtain. Recently, few-shot learning is gaining increasing popularity for this task, whereas these methods are sensitive to the inherent noise…

Cited by 0SourcePDFScholar
2023

CHMATCH: Contrastive Hierarchical Matching and Robust Adaptive Threshold Boosted Semi-Supervised Learning

CVPR 2023poster

The recently proposed FixMatch and FlexMatch have achieved remarkable results in the field of semi-supervised learning. But these two methods go to two extremes as FixMatch and FlexMatch use a pre-defined constant threshold for all classes and an adaptive threshold for each category, respectively. B…

2023

Self-adaptive Context and Modal-interaction Modeling For Multimodal Emotion Recognition

ACL 2023findings

The multimodal emotion recognition in conversation task aims to predict the emotion label for a given utterance with its context and multiple modalities. Existing approaches achieve good results but also suffer from the following two limitations: 1) lacking modeling of diverse dependency ranges, i.e…

Cited by 15SourcePDFScholar
2022

McQueen: a Benchmark for Multimodal Conversational Query Rewrite

EMNLP 2022main

The task of query rewrite aims to convert an in-context query to its fully-specified version where ellipsis and coreference are completed and referred-back according to the history context. Although much progress has been made, less efforts have been paid to real scenario conversations that involve…

2021

BiToD: A Bilingual Multi-Domain Dataset For Task-Oriented Dialogue Modeling

NeurIPS 2021poster

Task-oriented dialogue (ToD) benchmarks provide an important avenue to measure progress and develop better conversational agents. However, existing datasets for end-to-end ToD modeling are limited to a single language, hindering the development of robust end-to-end ToD systems for multilingual count…

Cited by 58SourcecodeScholar