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Found 28 papers, 2 papers with code
Few-Shot Table Understanding: A Benchmark Dataset and Pre-Training Baseline
Since there is no large number of public Chinese tables, we also collect a large-scale, multi-domain tabular corpus to facilitate future Chinese table pre-training, which includes one million tables and related natural language text with auxiliary supervised interaction signals.
Constructing Emotional Consensus and Utilizing Unpaired Data for Empathetic Dialogue Generation
To address the above issues, we propose a dual-generative model, Dual-Emp, to simultaneously construct the emotional consensus and utilize some external unpaired data.
CoLV: A Collaborative Latent Variable Model for Knowledge-Grounded Dialogue Generation
Knowledge-grounded dialogue generation has achieved promising performance with the engagement of external knowledge sources.
CodeGeeX: A Pre-Trained Model for Code Generation with Multilingual Evaluations on HumanEval-X
Large pre-trained code generation models, such as OpenAI Codex, can generate syntax- and function-correct code, making the coding of programmers more productive and our pursuit of artificial general intelligence closer.
Ranked #11 on
Code Generation
on HumanEval
DistilPose: Tokenized Pose Regression with Heatmap Distillation
Specifically, DistilPose maximizes the transfer of knowledge from the teacher model (heatmap-based) to the student model (regression-based) through Token-distilling Encoder (TDE) and Simulated Heatmaps.
CECT: Controllable Ensemble CNN and Transformer for COVID-19 Image Classification
To relieve model performance limitations due to the lack of global (local) features, we develop a novel classification network CECT by controllable ensemble CNN and transformer.
Differentially Private Natural Language Models: Recent Advances and Future Directions
In this paper, we provide the first systematic review of recent advances on DP deep learning models in NLP.
Coordinating Cross-modal Distillation for Molecular Property Prediction
The existing graph methods have demonstrated that 3D geometric information is significant for better performance in MPP.
MNER-QG: An End-to-End MRC framework for Multimodal Named Entity Recognition with Query Grounding
Multimodal named entity recognition (MNER) is a critical step in information extraction, which aims to detect entity spans and classify them to corresponding entity types given a sentence-image pair.
Recent Progress in Transformer-based Medical Image Analysis
In this review, we first recap the core component of the transformer, the attention mechanism, and the detailed structures of the transformer.
Geometric Synthesis: A Free lunch for Large-scale Palmprint Recognition Model Pretraining
In this paper, by observing that palmar creases are the key information to deep-learning-based palmprint recognition, we propose to synthesize training data by manipulating palmar creases.
GSDA: A Generative Adversarial Network-based Semi-Supervised Data Augmentation Method
The GSDA is composed of the GAN and Convolutional Neural Network (CNN), in which GAN synthesizes and pseudo-labeled the US images with high resolution and high quality, and both real and synthesized images are employed to train CNN.
Constructing Emotion Consensus and Utilizing Unpaired Data for Empathetic Dialogue Generation
To address the above issues, we propose a dual-generative model, Dual-Emp, to simultaneously construct the emotion consensus and utilize some external unpaired data.
Identifying Untrustworthy Samples: Data Filtering for Open-domain Dialogues with Bayesian Optimization
The training method updates parameters of a trained NCMs on two small sets with newly maintained and removed samples, respectively.
Text is NOT Enough: Integrating Visual Impressions into Open-domain Dialogue Generation
Specifically, we obtain a group of images (PVIs) for each post based on a pre-trained word-image mapping model.
GTM: A Generative Triple-Wise Model for Conversational Question Generation
Generating some appealing questions in open-domain conversations is an effective way to improve human-machine interactions and lead the topic to a broader or deeper direction.
Probing Product Description Generation via Posterior Distillation
To tackle this problem, we propose an adaptive posterior network based on Transformer architecture that can utilize user-cared information from customer reviews.
Learning to Select Context in a Hierarchical and Global Perspective for Open-domain Dialogue Generation
Open-domain multi-turn conversations mainly have three features, which are hierarchical semantic structure, redundant information, and long-term dependency.
User-Inspired Posterior Network for Recommendation Reason Generation
A simple and effective way is to extract keywords directly from the knowledge-base of products, i. e., attributes or title, as the recommendation reason.
Compose Like Humans: Jointly Improving the Coherence and Novelty for Modern Chinese Poetry Generation
Thus, it requires more to control the coherence and improve the novelty.
CDL: Curriculum Dual Learning for Emotion-Controllable Response Generation
Emotion-controllable response generation is an attractive and valuable task that aims to make open-domain conversations more empathetic and engaging.
The JDDC Corpus: A Large-Scale Multi-Turn Chinese Dialogue Dataset for E-commerce Customer Service
Human conversations are complicated and building a human-like dialogue agent is an extremely challenging task.
A Charge-Density-Wave Topological Semimetal
We here demonstrate that the room-temperature phase of (TaSe$_4$)$_2$I is a Weyl semimetal with 24 pairs of Weyl nodes.
Band Gap
Materials Science
Strongly Correlated Electrons
Accelerating Primal Solution Findings for Mixed Integer Programs Based on Solution Prediction
In many applications, a similar MIP model is solved on a regular basis, maintaining remarkable similarities in model structures and solution appearances but differing in formulation coefficients.
Modeling Semantic Relationship in Multi-turn Conversations with Hierarchical Latent Variables
Multi-turn conversations consist of complex semantic structures, and it is still a challenge to generate coherent and diverse responses given previous utterances.
Intrinsic Ferromagnetism in Electrenes
We report intrinsic ferromagnetism in monolayer electrides or electrenes, in which excess electrons act as anions.
Computational Physics Materials Science
Speeding Up Neural Machine Translation Decoding by Cube Pruning
Although neural machine translation has achieved promising results, it suffers from slow translation speed.
Empirical Evaluation of RNN Architectures on Sentence Classification Task
Recurrent Neural Networks have achieved state-of-the-art results for many problems in NLP and two most popular RNN architectures are Tail Model and Pooling Model.
