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Found 32 papers, 14 papers with code
CausalCellSegmenter: Causal Inference inspired Diversified Aggregation Convolution for Pathology Image Segmentation
Deep learning models have shown promising performance for cell nucleus segmentation in the field of pathology image analysis.
Enhancing User Intent Capture in Session-Based Recommendation with Attribute Patterns
The goal of session-based recommendation in E-commerce is to predict the next item that an anonymous user will purchase based on the browsing and purchase history.
Situated Natural Language Explanations
Situated NLE provides a perspective and facilitates further research on the generation and evaluation of explanations.
TextPainter: Multimodal Text Image Generation with Visual-harmony and Text-comprehension for Poster Design
Specifically, TextPainter takes the global-local background image as a hint of style and guides the text image generation with visual harmony.
AutoPoster: A Highly Automatic and Content-aware Design System for Advertising Poster Generation
Meanwhile, to our knowledge, we propose the first poster generation dataset that includes visual attribute annotations for over 76k posters.
DeSAM: Decoupling Segment Anything Model for Generalizable Medical Image Segmentation
In fully automatic mode, the presence of inevitable poor prompts (such as points outside the mask or boxes significantly larger than the mask) can significantly mislead mask generation.
Graph Reasoning for Question Answering with Triplet Retrieval
State-of-the-art methods often utilize entities in questions to retrieve local subgraphs, which are then fed into KG encoder, e. g. graph neural networks (GNNs), to model their local structures and integrated into language models for question answering.
CCGen: Explainable Complementary Concept Generation in E-Commerce
We propose and study Complementary Concept Generation (CCGen): given a concept of interest, e. g., "Digital Cameras", generating a list of complementary concepts, e. g., 1) Camera Lenses 2) Batteries 3) Camera Cases 4) Memory Cards 5) Battery Chargers.
SCOTT: Self-Consistent Chain-of-Thought Distillation
While CoT can yield dramatically improved performance, such gains are only observed for sufficiently large LMs.
FolkScope: Intention Knowledge Graph Construction for E-commerce Commonsense Discovery
Understanding users' intentions in e-commerce platforms requires commonsense knowledge.
The ProfessionAl Go annotation datasEt (PAGE)
To the best of our knowledge, PAGE is the first dataset with extensive annotation in the game of Go.
An Anatomy-aware Framework for Automatic Segmentation of Parotid Tumor from Multimodal MRI
Second, considering that the segmentation model is prone to be disturbed by similar anatomical structures and make wrong predictions, we design anatomy-aware loss.
Improving Task Generalization via Unified Schema Prompt
Task generalization has been a long standing challenge in Natural Language Processing (NLP).
Retrieval-Augmented Multilingual Keyphrase Generation with Retriever-Generator Iterative Training
Keyphrase generation is the task of automatically predicting keyphrases given a piece of long text.
ProQA: Structural Prompt-based Pre-training for Unified Question Answering
Furthermore, ProQA exhibits strong ability in both continual learning and transfer learning by taking the advantages of the structural prompt.
PGD: A Large-scale Professional Go Dataset for Data-driven Analytics
This paper creates the Professional Go Dataset (PGD), containing 98, 043 games played by 2, 148 professional players from 1950 to 2021.
Mutual Attention-based Hybrid Dimensional Network for Multimodal Imaging Computer-aided Diagnosis
Recent works on Multimodal 3D Computer-aided diagnosis have demonstrated that obtaining a competitive automatic diagnosis model when a 3D convolution neural network (CNN) brings more parameters and medical images are scarce remains nontrivial and challenging.
TransMed: Transformers Advance Multi-modal Medical Image Classification
To our best knowledge, this is the first work to apply transformers to medical image classification.
Open-Retrieval Conversational Machine Reading
On our created OR-ShARC dataset, MUDERN achieves the state-of-the-art performance, outperforming existing single-passage conversational machine reading models as well as a new multi-passage conversational machine reading baseline by a large margin.
Leveraging WordNet Paths for Neural Hypernym Prediction
We formulate the problem of hypernym prediction as a sequence generation task, where the sequences are taxonomy paths in WordNet.
Answering Ambiguous Questions through Generative Evidence Fusion and Round-Trip Prediction
When multiple plausible answers are found, the system should rewrite the question for each answer to resolve the ambiguity.
Discern: Discourse-Aware Entailment Reasoning Network for Conversational Machine Reading
Based on the learned EDU and entailment representations, we either reply to the user our final decision "yes/no/irrelevant" of the initial question, or generate a follow-up question to inquiry more information.
Dialogue Generation on Infrequent Sentence Functions via Structured Meta-Learning
Besides a small number of high-resource sentence functions, a large portion of sentence functions is infrequent.
Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading
The goal of conversational machine reading is to answer user questions given a knowledge base text which may require asking clarification questions.
EMT: Explicit Memory Tracker with Coarse-to-Fine Reasoning for Conversational Machine Reading
The goal of conversational machine reading is to answer user questions given a knowledge base text which may require asking clarification questions.
Non-linearity identification for construction workers' personality-safety behaviour predictive relationship using neural network and linear regression modelling
The latest literature has evidenced that there is within-population diversity that leads people's intended safety behaviours in the workplace, which are found to vary among individuals as a function of their personality traits.
Improving Question Generation With to the Point Context
Question generation (QG) is the task of generating a question from a reference sentence and a specified answer within the sentence.
Interconnected Question Generation with Coreference Alignment and Conversation Flow Modeling
The coreference alignment modeling explicitly aligns coreferent mentions in conversation history with corresponding pronominal references in generated questions, which makes generated questions interconnected to conversation history.
Generating Distractors for Reading Comprehension Questions from Real Examinations
We investigate the task of distractor generation for multiple choice reading comprehension questions from examinations.
Title-Guided Encoding for Keyphrase Generation
Keyphrase generation (KG) aims to generate a set of keyphrases given a document, which is a fundamental task in natural language processing (NLP).
Difficulty Controllable Generation of Reading Comprehension Questions
We investigate the difficulty levels of questions in reading comprehension datasets such as SQuAD, and propose a new question generation setting, named Difficulty-controllable Question Generation (DQG).
Learning Multi-level Features For Sensor-based Human Action Recognition
This paper proposes a multi-level feature learning framework for human action recognition using a single body-worn inertial sensor.
