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Found 22 papers, 9 papers with code
S^2SQL: Injecting Syntax to Question-Schema Interaction Graph Encoder for Text-to-SQL Parsers
The task of converting a natural language question into an executable SQL query, known as text-to-SQL, is an important branch of semantic parsing.
C$^2$LEVA: Toward Comprehensive and Contamination-Free Language Model Evaluation
Recent advances in large language models (LLMs) have shown significant promise, yet their evaluation raises concerns, particularly regarding data contamination due to the lack of access to proprietary training data.
Making Long-Context Language Models Better Multi-Hop Reasoners
Recent advancements in long-context modeling have enhanced language models (LMs) for complex tasks across multiple NLP applications.
VL-PET: Vision-and-Language Parameter-Efficient Tuning via Granularity Control
In particular, our VL-PET-large with lightweight PET module designs significantly outperforms VL-Adapter by 2. 92% (3. 41%) and LoRA by 3. 37% (7. 03%) with BART-base (T5-base) on image-text tasks.
CLEVA: Chinese Language Models EVAluation Platform
With the continuous emergence of Chinese Large Language Models (LLMs), how to evaluate a model's capabilities has become an increasingly significant issue.
Multi-Path Transformer is Better: A Case Study on Neural Machine Translation
For years the model performance in machine learning obeyed a power-law relationship with the model size.
SPRING: Situated Conversation Agent Pretrained with Multimodal Questions from Incremental Layout Graph
Existing multimodal conversation agents have shown impressive abilities to locate absolute positions or retrieve attributes in simple scenarios, but they fail to perform well when complex relative positions and information alignments are involved, which poses a bottleneck in response quality.
Eliciting Knowledge from Large Pre-Trained Models for Unsupervised Knowledge-Grounded Conversation
Recent advances in large-scale pre-training provide large models with the potential to learn knowledge from the raw text.
Knowledgeable Salient Span Mask for Enhancing Language Models as Knowledge Base
Pre-trained language models (PLMs) like BERT have made significant progress in various downstream NLP tasks.
Probing Structured Pruning on Multilingual Pre-trained Models: Settings, Algorithms, and Efficiency
Structured pruning has been extensively studied on monolingual pre-trained language models and is yet to be fully evaluated on their multilingual counterparts.
FlowEval: A Consensus-Based Dialogue Evaluation Framework Using Segment Act Flows
Hence, we propose segment act, an extension of dialog act from utterance level to segment level, and crowdsource a large-scale dataset for it.
The NiuTrans System for WNGT 2020 Efficiency Task
This paper describes the submissions of the NiuTrans Team to the WNGT 2020 Efficiency Shared Task.
Bag of Tricks for Optimizing Transformer Efficiency
Improving Transformer efficiency has become increasingly attractive recently.
Stacked Acoustic-and-Textual Encoding: Integrating the Pre-trained Models into Speech Translation Encoders
To our knowledge, we are the first to develop an end-to-end ST system that achieves comparable or even better BLEU performance than the cascaded ST counterpart when large-scale ASR and MT data is available.
Automatic Speech Recognition
Automatic Speech Recognition (ASR)
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An Efficient Transformer Decoder with Compressed Sub-layers
The large attention-based encoder-decoder network (Transformer) has become prevailing recently due to its effectiveness.
A Simple and Effective Approach to Robust Unsupervised Bilingual Dictionary Induction
Our experiments show that this simple method does not hamper the performance of similar language pairs and achieves an accuracy of 13. 64~55. 53% between English and four distant languages, i. e., Chinese, Japanese, Vietnamese and Thai.
Weight Distillation: Transferring the Knowledge in Neural Network Parameters
Inspired by this, we investigate methods of model acceleration and compression in another line of research.
Towards Fully 8-bit Integer Inference for the Transformer Model
8-bit integer inference, as a promising direction in reducing both the latency and storage of deep neural networks, has made great progress recently.
Neural Machine Translation with Joint Representation
Though early successes of Statistical Machine Translation (SMT) systems are attributed in part to the explicit modelling of the interaction between any two source and target units, e. g., alignment, the recent Neural Machine Translation (NMT) systems resort to the attention which partially encodes the interaction for efficiency.
Multi-layer Representation Fusion for Neural Machine Translation
In this paper, we propose a multi-layer representation fusion (MLRF) approach to fusing stacked layers.
The NiuTrans Machine Translation Systems for WMT19
We participated in 13 translation directions, including 11 supervised tasks, namely EN↔{ZH, DE, RU, KK, LT}, GU→EN and the unsupervised DE↔CS sub-track.
A Simple and Effective Approach to Coverage-Aware Neural Machine Translation
We offer a simple and effective method to seek a better balance between model confidence and length preference for Neural Machine Translation (NMT).
