Search Results for author:
Found 30 papers, 7 papers with code
An Attention-Based Denoising Framework for Personality Detection in Social Media Texts
In social media networks, users produce a large amount of text content anytime, providing researchers with a valuable approach to digging for personality-related information.
Ask One More Time: Self-Agreement Improves Reasoning of Language Models in (Almost) All Scenarios
Although chain-of-thought (CoT) prompting combined with language models has achieved encouraging results on complex reasoning tasks, the naive greedy decoding used in CoT prompting usually causes the repetitiveness and local optimality.
Skywork: A More Open Bilingual Foundation Model
In this technical report, we present Skywork-13B, a family of large language models (LLMs) trained on a corpus of over 3. 2 trillion tokens drawn from both English and Chinese texts.
SkyMath: Technical Report
Large language models (LLMs) have shown great potential to solve varieties of natural language processing (NLP) tasks, including mathematical reasoning.
KwaiYiiMath: Technical Report
Recent advancements in large language models (LLMs) have demonstrated remarkable abilities in handling a variety of natural language processing (NLP) downstream tasks, even on mathematical tasks requiring multi-step reasoning.
Ranked #87 on
Arithmetic Reasoning
on GSM8K
(using extra training data)
Layer-wise Representation Fusion for Compositional Generalization
Inspired by this, we propose LRF, a novel \textbf{L}ayer-wise \textbf{R}epresentation \textbf{F}usion framework for CG, which learns to fuse previous layers' information back into the encoding and decoding process effectively through introducing a \emph{fuse-attention module} at each encoder and decoder layer.
Learning to Compose Representations of Different Encoder Layers towards Improving Compositional Generalization
There is mounting evidence that one of the reasons hindering CG is the representation of the encoder uppermost layer is entangled, i. e., the syntactic and semantic representations of sequences are entangled.
LEAPT: Learning Adaptive Prefix-to-prefix Translation For Simultaneous Machine Translation
Simultaneous machine translation, which aims at a real-time translation, is useful in many live scenarios but very challenging due to the trade-off between accuracy and latency.
Spatio-temporal Tendency Reasoning for Human Body Pose and Shape Estimation from Videos
Different from them, our STR aims to learn accurate and natural motion sequences in an unconstrained environment through temporal and spatial tendency and to fully excavate the spatio-temporal features of existing video data.
Ranked #55 on
3D Human Pose Estimation
on MPI-INF-3DHP
Network-wide Multi-step Traffic Volume Prediction using Graph Convolutional Gated Recurrent Neural Network
For instance, our model reduces MAE by 25. 3%, RMSE by 29. 2%, and MAPE by 20. 2%, compared to the state-of-the-art Diffusion Convolutional Recurrent Neural Network (DCRNN) model using the hourly dataset.
Trend and Thoughts: Understanding Climate Change Concern using Machine Learning and Social Media Data
Nowadays social media platforms such as Twitter provide a great opportunity to understand public opinion of climate change compared to traditional survey methods.
Robust Ensembling Network for Unsupervised Domain Adaptation
In this paper, we propose a Robust Ensembling Network (REN) for UDA, which applies a robust time ensembling teacher network to learn global information for domain transfer.
ITNLP at SemEval-2021 Task 11: Boosting BERT with Sampling and Adversarial Training for Knowledge Extraction
This paper describes the winning system in the End-to-end Pipeline phase for the NLPContributionGraph task.
KuiLeiXi: a Chinese Open-Ended Text Adventure Game
Equipped with GPT-2 and the latest GPT-3, AI Dungeon has been seen as a famous example of the powerful text generation capabilities of large-scale pre-trained language models, and a possibility for future games.
MDQE: A More Accurate Direct Pretraining for Machine Translation Quality Estimation
However, we argue that there are still gaps between the predictor and the estimator in both data quality and training objectives, which preclude QE models from benefiting from a large number of parallel corpora more directly.
Neural Process for Black-Box Model Optimization Under Bayesian Framework
In order to validate the benefits of NPBO, we compare NPBO with four benchmark approaches on a power system parameter optimization problem and a series of seven benchmark Bayesian optimization problems.
MCFlow: Monte Carlo Flow Models for Data Imputation
We consider the topic of data imputation, a foundational task in machine learning that addresses issues with missing data.
Medical Time Series Classification with Hierarchical Attention-based Temporal Convolutional Networks: A Case Study of Myotonic Dystrophy Diagnosis
Myotonia, which refers to delayed muscle relaxation after contraction, is the main symptom of myotonic dystrophy patients.
YouTube AV 50K: An Annotated Corpus for Comments in Autonomous Vehicles
With one billion monthly viewers, and millions of users discussing and sharing opinions, comments below YouTube videos are rich sources of data for opinion mining and sentiment analysis.
ITNLP-ARC at SemEval-2018 Task 12: Argument Reasoning Comprehension with Attention
Semantic Evaluation (SemEval) 2018 Task 12 {``}The Argument Reasoning Comprehension{''} committed to research natural language reasoning.
Predicting Station-level Hourly Demands in a Large-scale Bike-sharing Network: A Graph Convolutional Neural Network Approach
Two architectures of the GCNN-DDGF model are explored; GCNNreg-DDGF is a regular GCNN-DDGF model which contains the convolution and feedforward blocks, and GCNNrec-DDGF additionally contains a recurrent block from the Long Short-term Memory neural network architecture to capture temporal dependencies in the bike-sharing demand series.
Reliability and Sharpness in Border Crossing Traffic Interval Prediction
Short-term traffic volume prediction models have been extensively studied in the past few decades.
Abnormal Spatial-Temporal Pattern Analysis for Niagara Frontier Border Wait Times
It can identify the abnormal spatial-temporal patterns for both passenger vehicles and trucks at three bridges connecting US and Canada.
ITNLP-AiKF at SemEval-2017 Task 1: Rich Features Based SVR for Semantic Textual Similarity Computing
Semantic Textual Similarity (STS) devotes to measuring the degree of equivalence in the underlying semantic of the sentence pair.
Real-time Traffic Accident Risk Prediction based on Frequent Pattern Tree
Both the proposed method based on the FP tree algorithm, as well as the widely utilized, random forest method, were then used to identify the important variables or the Virginia dataset.
Learning Natural Language Inference using Bidirectional LSTM model and Inner-Attention
In our approach, the encoding of sentence is a two-stage process.
Ranked #73 on
Natural Language Inference
on SNLI
Radical-Enhanced Chinese Character Embedding
We present a method to leverage radical for learning Chinese character embedding.
