2 citations · 4 across the 7 of their papers we have counts for
7 papers · 1 filter
A Unified Data Augmentation Framework for Low-Resource Multi-Domain Dialogue Generation
Yongkang Liu, Ercong Nie, Shi Feng +5
Current state-of-the-art dialogue systems heavily rely on extensive training datasets. However, challenges arise in domains where domain-specific training datasets are insufficient…
Decoding Probing: Revealing Internal Linguistic Structures in Neural Language Models using Minimal Pairs
Linyang He, Peili Chen, Ercong Nie +2
Inspired by cognitive neuroscience studies, we introduce a novel `decoding probing' method that uses minimal pairs benchmark (BLiMP) to probe internal linguistic characteristics in…
ToPro: Token-Level Prompt Decomposition for Cross-Lingual Sequence Labeling Tasks
Bolei Ma, Ercong Nie, Shuzhou Yuan +4
Prompt-based methods have been successfully applied to multilingual pretrained language models for zero-shot cross-lingual understanding. However, most previous studies primarily f…
Unleashing the Multilingual Encoder Potential: Boosting Zero-Shot Performance via Probability Calibration
Ercong Nie, Helmut Schmid, Hinrich Schütze
Pretrained multilingual encoder models can directly perform zero-shot multilingual tasks or linguistic probing by reformulating the input examples into cloze-style prompts. This is…
Cross-Lingual Constituency Parsing for Middle High German: A Delexicalized Approach
Ercong Nie, Helmut Schmid, Hinrich Schütze
Constituency parsing plays a fundamental role in advancing natural language processing (NLP) tasks. However, training an automatic syntactic analysis system for ancient languages s…
Baby's CoThought: Leveraging Large Language Models for Enhanced Reasoning in Compact Models
Zheyu Zhang, Han Yang, Bolei Ma +2
Large Language Models (LLMs) demonstrate remarkable performance on a variety of natural language understanding (NLU) tasks, primarily due to their in-context learning ability. This…