57 citations · 189 across the 21 of their papers we have counts for
21 papers
Long-form RewardBench: Evaluating Reward Models for Long-form Generation
Hui Huang, Yancheng He, Wei Liu +7
The widespread adoption of reinforcement learning-based alignment highlights the growing importance of reward models. Various benchmarks have been built to evaluate reward models i…
Toward Robust LLM-Based Judges: Taxonomic Bias Evaluation and Debiasing Optimization
Hongli Zhou, Hui Huang, Rui Zhang +5
Large language model (LLM)-based judges are widely adopted for automated evaluation and reward modeling, yet their judgments are often affected by judgment biases. Accurately evalu…
From Perception to Reasoning: Deep Thinking Empowers Multimodal Large Language Models
Wenxin Zhu, Andong Chen, Yuchen Song +4
With the remarkable success of Multimodal Large Language Models (MLLMs) in perception tasks, enhancing their complex reasoning capabilities has emerged as a critical research focus…
Lost in Benchmarks? Rethinking Large Language Model Benchmarking with Item Response Theory
Hongli Zhou, Hui Huang, Ziqing Zhao +10
The evaluation of large language models (LLMs) via benchmarks is widespread, yet inconsistencies between different leaderboards and poor separability among top models raise concern…
Universal Multimodal Representation for Language Understanding
Zhuosheng Zhang, Kehai Chen, Rui Wang +4
Representation learning is the foundation of natural language processing (NLP). This work presents new methods to employ visual information as assistant signals to general NLP task…
Document-Level Relation Extraction with Sentences Importance Estimation and Focusing
Wang Xu, Kehai Chen, Lili Mou +1
Document-level relation extraction (DocRE) aims to determine the relation between two entities from a document of multiple sentences. Recent studies typically represent the entire…
Text Compression-aided Transformer Encoding
Zuchao Li, Zhuosheng Zhang, Hai Zhao +4
Text encoding is one of the most important steps in Natural Language Processing (NLP). It has been done well by the self-attention mechanism in the current state-of-the-art Transfo…
Document-Level Relation Extraction with Reconstruction
Wang Xu, Kehai Chen, Tiejun Zhao
In document-level relation extraction (DocRE), graph structure is generally used to encode relation information in the input document to classify the relation category between each…
SJTU-NICT's Supervised and Unsupervised Neural Machine Translation Systems for the WMT20 News Translation Task
Zuchao Li, Hai Zhao, Rui Wang +3
In this paper, we introduced our joint team SJTU-NICT 's participation in the WMT 2020 machine translation shared task. In this shared task, we participated in four translation dir…
Document-level Neural Machine Translation with Document Embeddings
Shu Jiang, Hai Zhao, Zuchao Li +1
Standard neural machine translation (NMT) is on the assumption of document-level context independent. Most existing document-level NMT methods are satisfied with a smattering sense…
Knowledge Distillation for Multilingual Unsupervised Neural Machine Translation
Haipeng Sun, Rui Wang, Kehai Chen +3
Unsupervised neural machine translation (UNMT) has recently achieved remarkable results for several language pairs. However, it can only translate between a single language pair an…
Explicit Reordering for Neural Machine Translation
Kehai Chen, Rui Wang, Masao Utiyama +1
In Transformer-based neural machine translation (NMT), the positional encoding mechanism helps the self-attention networks to learn the source representation with order dependency,…
Self-Training for Unsupervised Neural Machine Translation in Unbalanced Training Data Scenarios
Haipeng Sun, Rui Wang, Kehai Chen +3
Unsupervised neural machine translation (UNMT) that relies solely on massive monolingual corpora has achieved remarkable results in several translation tasks. However, in real-worl…
Modeling Future Cost for Neural Machine Translation
Chaoqun Duan, Kehai Chen, Rui Wang +4
Existing neural machine translation (NMT) systems utilize sequence-to-sequence neural networks to generate target translation word by word, and then make the generated word at each…
Robust Unsupervised Neural Machine Translation with Adversarial Denoising Training
Haipeng Sun, Rui Wang, Kehai Chen +4
Unsupervised neural machine translation (UNMT) has recently attracted great interest in the machine translation community. The main advantage of the UNMT lies in its easy collectio…
Explicit Sentence Compression for Neural Machine Translation
Zuchao Li, Rui Wang, Kehai Chen +4
State-of-the-art Transformer-based neural machine translation (NMT) systems still follow a standard encoder-decoder framework, in which source sentence representation can be well d…
Probing Contextualized Sentence Representations with Visual Awareness
Zhuosheng Zhang, Rui Wang, Kehai Chen +3
We present a universal framework to model contextualized sentence representations with visual awareness that is motivated to overcome the shortcomings of the multimodal parallel da…
Document-level Neural Machine Translation with Associated Memory Network
Shu Jiang, Rui Wang, Zuchao Li +5
Standard neural machine translation (NMT) is on the assumption that the document-level context is independent. Most existing document-level NMT approaches are satisfied with a smat…
Revisiting Simple Domain Adaptation Methods in Unsupervised Neural Machine Translation
Haipeng Sun, Rui Wang, Kehai Chen +4
Domain adaptation has been well-studied in supervised neural machine translation (SNMT). However, it has not been well-studied for unsupervised neural machine translation (UNMT), a…
Lattice-Based Transformer Encoder for Neural Machine Translation
Fengshun Xiao, Jiangtong Li, Hai Zhao +2
Neural machine translation (NMT) takes deterministic sequences for source representations. However, either word-level or subword-level segmentations have multiple choices to split…
Syntax-Directed Attention for Neural Machine Translation
Kehai Chen, Rui Wang, Masao Utiyama +2
Attention mechanism, including global attention and local attention, plays a key role in neural machine translation (NMT). Global attention attends to all source words for word pre…