8 citations · 30 across the 16 of their papers we have counts for
16 papers
Judge Like Human Examiners: A Weighted Importance Multi-Point Evaluation Framework for Generative Tasks with Long-form Answers
Guoxin Yu, Chulun Zhou, Lemao Liu +7
Evaluating the quality of model responses remains challenging in generative tasks with long-form answers, as the expected answers usually contain multiple semantically distinct yet…
HGMEM: Hypergraph-based Working Memory to Improve Multi-step RAG for Long-Context Complex Relational Modeling
Chulun Zhou, Chunkang Zhang, Guoxin Yu +4
Multi-step retrieval-augmented generation (RAG) has become a widely adopted strategy for enhancing large language models (LLMs) on tasks that demand global comprehension and intens…
PRELUDE: A Benchmark Designed to Require Global Comprehension and Reasoning over Long Contexts
Mo Yu, Tsz Ting Chung, Chulun Zhou +8
We introduce PRELUDE, a benchmark for evaluating long-context understanding through the task of determining whether a character's prequel story is consistent with the canonical nar…
The Essence of Contextual Understanding in Theory of Mind: A Study on Question Answering with Story Characters
Chulun Zhou, Qiujing Wang, Mo Yu +7
Theory-of-Mind (ToM) is a fundamental psychological capability that allows humans to understand and interpret the mental states of others. Humans infer others' thoughts by integrat…
RC3: Regularized Contrastive Cross-lingual Cross-modal Pre-training
Chulun Zhou, Yunlong Liang, Fandong Meng +3
Multilingual vision-language (V&L) pre-training has achieved remarkable progress in learning universal representations across different modalities and languages. In spite of recent…
A Multi-task Multi-stage Transitional Training Framework for Neural Chat Translation
Chulun Zhou, Yunlong Liang, Fandong Meng +5
Neural chat translation (NCT) aims to translate a cross-lingual chat between speakers of different languages. Existing context-aware NMT models cannot achieve satisfactory performa…
Getting the Most out of Simile Recognition
Xiaoyue Wang, Linfeng Song, Xin Liu +2
Simile recognition involves two subtasks: simile sentence classification that discriminates whether a sentence contains simile, and simile component extraction that locates the cor…
Towards Robust k-Nearest-Neighbor Machine Translation
Hui Jiang, Ziyao Lu, Fandong Meng +4
k-Nearest-Neighbor Machine Translation (kNN-MT) becomes an important research direction of NMT in recent years. Its main idea is to retrieve useful key-value pairs from an addition…
A Variational Hierarchical Model for Neural Cross-Lingual Summarization
Yunlong Liang, Fandong Meng, Chulun Zhou +4
The goal of the cross-lingual summarization (CLS) is to convert a document in one language (e.g., English) to a summary in another one (e.g., Chinese). Essentially, the CLS task is…
Confidence Based Bidirectional Global Context Aware Training Framework for Neural Machine Translation
Chulun Zhou, Fandong Meng, Jie Zhou +3
Most dominant neural machine translation (NMT) models are restricted to make predictions only according to the local context of preceding words in a left-to-right manner. Although…
Towards Making the Most of Dialogue Characteristics for Neural Chat Translation
Yunlong Liang, Chulun Zhou, Fandong Meng +4
Neural Chat Translation (NCT) aims to translate conversational text between speakers of different languages. Despite the promising performance of sentence-level and context-aware n…
Exploring Dynamic Selection of Branch Expansion Orders for Code Generation
Hui Jiang, Chulun Zhou, Fandong Meng +5
Due to the great potential in facilitating software development, code generation has attracted increasing attention recently. Generally, dominant models are Seq2Tree models, which…
A Novel Graph-based Multi-modal Fusion Encoder for Neural Machine Translation
Yongjing Yin, Fandong Meng, Jinsong Su +4
Multi-modal neural machine translation (NMT) aims to translate source sentences into a target language paired with images. However, dominant multi-modal NMT models do not fully exp…
Modeling Discourse Structure for Document-level Neural Machine Translation
Junxuan Chen, Xiang Li, Jiarui Zhang +4
Recently, document-level neural machine translation (NMT) has become a hot topic in the community of machine translation. Despite its success, most of existing studies ignored the…
Exploring Contextual Word-level Style Relevance for Unsupervised Style Transfer
Chulun Zhou, Liangyu Chen, Jiachen Liu +4
Unsupervised style transfer aims to change the style of an input sentence while preserving its original content without using parallel training data. In current dominant approaches…
Graph-based Neural Sentence Ordering
Yongjing Yin, Linfeng Song, Jinsong Su +3
Sentence ordering is to restore the original paragraph from a set of sentences. It involves capturing global dependencies among sentences regardless of their input order. In this p…