5 papers
One Model, Multiple Goals: Adaptive Multi-Objective Learning for E-commerce Dialogue Systems
Mingzhe Li, Jing Xiang, Enguo Zhou +5
Dialogue systems in e-commerce scenarios often need to satisfy multiple objectives: accurately reasoning over user profiles (e.g., eligibility, credit limit) to ensure correct deci…
Flipping Knowledge Distillation: Leveraging Small Models' Expertise to Enhance LLMs in Text Matching
Mingzhe Li, Jing Xiang, Qishen Zhang +2
Knowledge distillation typically involves transferring knowledge from a Large Language Model (LLM) to a Smaller Language Model (SLM). However, in tasks such as text matching, fine-…
Keywords and Instances: A Hierarchical Contrastive Learning Framework Unifying Hybrid Granularities for Text Generation
Mingzhe Li, XieXiong Lin, Xiuying Chen +8
Contrastive learning has achieved impressive success in generation tasks to militate the "exposure bias" problem and discriminatively exploit the different quality of references. E…
Detoxifying Large Language Models via Knowledge Editing
Mengru Wang, Ningyu Zhang, Ziwen Xu +7
This paper investigates using knowledge editing techniques to detoxify Large Language Models (LLMs). We construct a benchmark, SafeEdit, which covers nine unsafe categories with va…
Multi-Intent Attribute-Aware Text Matching in Searching
Mingzhe Li, Xiuying Chen, Jing Xiang +6
Text matching systems have become a fundamental service in most searching platforms. For instance, they are responsible for matching user queries to relevant candidate items, or re…