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Found 22 papers, 6 papers with code
A Contrastive Framework for Learning Sentence Representations from Pairwise and Triple-wise Perspective in Angular Space
Learning high-quality sentence representations is a fundamental problem of natural language processing which could benefit a wide range of downstream tasks.
ZHIXIAOBAO at SemEval-2022 Task 10: Apporoaching Structured Sentiment with Graph Parsing
This paper presents our submission to task 10, Structured Sentiment Analysis of the SemEval 2022 competition.
BezierFormer: A Unified Architecture for 2D and 3D Lane Detection
B\'{e}zierFormer formulate queries as B\'{e}zier control points and incorporate a novel B\'{e}zier curve attention mechanism.
Box2Poly: Memory-Efficient Polygon Prediction of Arbitrarily Shaped and Rotated Text
Recently, Transformer-based text detection techniques have sought to predict polygons by encoding the coordinates of individual boundary vertices using distinct query features.
NeMO: Neural Map Growing System for Spatiotemporal Fusion in Bird's-Eye-View and BDD-Map Benchmark
We also provide a new scene-level BEV map evaluation setting along with the corresponding baseline for a more comprehensive comparison.
Towards Personalized Review Summarization by Modeling Historical Reviews from Customer and Product Separately
Review summarization is a non-trivial task that aims to summarize the main idea of the product review in the E-commerce website.
IPPO: Obstacle Avoidance for Robotic Manipulators in Joint Space via Improved Proximal Policy Optimization
Additionally, to enhance the performance of the model in reaching tasks, we introduce the action ensembles method and design the policy to directly participate in value function updates in PPO.
GEN-VLKT: Simplify Association and Enhance Interaction Understanding for HOI Detection
In this paper, we reveal and address the disadvantages of the conventional query-driven HOI detectors from the two aspects.
Ranked #12 on
Human-Object Interaction Detection
on HICO-DET
Utterance Rewriting with Contrastive Learning in Multi-turn Dialogue
Context modeling plays a significant role in building multi-turn dialogue systems.
Towards Generalized Models for Task-oriented Dialogue Modeling on Spoken Conversations
Building robust and general dialogue models for spoken conversations is challenging due to the gap in distributions of spoken and written data.
Precognition in Task-oriented Dialogue Understanding: Posterior Regularization by Future Context
And only historical information is used for inference.
HeteroQA: Learning towards Question-and-Answering through Multiple Information Sources via Heterogeneous Graph Modeling
Most of the CQA methods only incorporate articles or Wikipedia to extract knowledge and answer the user's question.
S+PAGE: A Speaker and Position-Aware Graph Neural Network Model for Emotion Recognition in Conversation
Emotion recognition in conversation (ERC) has attracted much attention in recent years for its necessity in widespread applications.
Ranked #1 on
Emotion Recognition in Conversation
on DailyDialog
RIO: Rotation-equivariance supervised learning of robust inertial odometry
This paper introduces rotation-equivariance as a self-supervisor to train inertial odometry models.
Measuring Uncertainty in Signal Fingerprinting with Gaussian Processes Going Deep
In indoor positioning, signal fluctuation is highly location-dependent.
Mining the Benefits of Two-stage and One-stage HOI Detection
To this end, we propose a novel one-stage framework with disentangling human-object detection and interaction classification in a cascade manner.
Ranked #7 on
Human-Object Interaction Detection
on V-COCO
Relation Aware Semi-autoregressive Semantic Parsing for NL2SQL
It first learns relation embedding over the schema entities and question words with predefined schema relations with ELECTRA and relation aware transformer layer as backbone.
SeaD: End-to-end Text-to-SQL Generation with Schema-aware Denoising
In text-to-SQL task, seq-to-seq models often lead to sub-optimal performance due to limitations in their architecture.
Stick to the Facts: Learning towards a Fidelity-oriented E-Commerce Product Description Generation
Different from other text generation tasks, in product description generation, it is of vital importance to generate faithful descriptions that stick to the product attribute information.
Improve Diverse Text Generation by Self Labeling Conditional Variational Auto Encoder
In fact, this objective term guides the encoder towards the "best encoder" of the decoder to enhance the expressiveness.
Orthogonal Weight Normalization: Solution to Optimization overMultiple Dependent Stiefel Manifolds in Deep Neural Networks
In this paper, we generalize such square orthogonal matrix to orthogonal rectangular matrix and formulating this problem in feed-forward Neural Networks (FNNs) as Optimization over Multiple Dependent Stiefel Manifolds (OMDSM).
Orthogonal Weight Normalization: Solution to Optimization over Multiple Dependent Stiefel Manifolds in Deep Neural Networks
In this paper, we generalize such square orthogonal matrix to orthogonal rectangular matrix and formulating this problem in feed-forward Neural Networks (FNNs) as Optimization over Multiple Dependent Stiefel Manifolds (OMDSM).
