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Found 55 papers, 27 papers with code
A Simple Model for Distantly Supervised Relation Extraction
Our BGM comprises of an instance embedding module and a bag representation module.
Enhanced Multi-Channel Graph Convolutional Network for Aspect Sentiment Triplet Extraction
Specifically, we first define ten types of relations for ASTE task, and then adopt a biaffine attention module to embed these relations as an adjacent tensor between words in a sentence.
Grouped-Attention for Content-Selection and Content-Plan Generation
A key component of the GSC-attention is grouped-attention, which is token-level attention constrained within each input attribute that enables our proposed model captures both local and global context.
Task-Oriented Clustering for Dialogues
A reliable clustering algorithm for task-oriented dialogues can help developer analysis and define dialogue tasks efficiently.
DialogueTRM: Exploring Multi-Modal Emotional Dynamics in a Conversation
Emotion dynamics formulates principles explaining the emotional fluctuation during conversations.
Learn to Adapt for Generalized Zero-Shot Text Classification
Generalized zero-shot text classification aims to classify textual instances from both previously seen classes and incrementally emerging unseen classes.
DiffHarmony: Latent Diffusion Model Meets Image Harmonization
To deal with these issues, in this paper, we first adapt a pre-trained latent diffusion model to the image harmonization task to generate the harmonious but potentially blurry initial images.
In-context Prompt Learning for Test-time Vision Recognition with Frozen Vision-language Model
To this end, we explore the concept of test-time prompt tuning (TTPT), which enables the adaptation of the CLIP model to novel downstream tasks through only one step of optimization on an unsupervised objective that involves the test sample.
Towards Robustness Analysis of E-Commerce Ranking System
As e-commerce retailers use various techniques to improve the quality of search results, we hope that this research offers valuable guidance for measuring the robustness of the ranking systems.
Joint User Association, Interference Cancellation and Power Control for Multi-IRS Assisted UAV Communications
To address the aforementioned challenges, we propose a new optimization algorithm for joint IRS-user association, trajectory optimization of UAVs, successive interference cancellation (SIC) decoding order scheduling and power allocation to maximize system energy efficiency.
A Survey on Trustworthy Edge Intelligence: From Security and Reliability To Transparency and Sustainability
Edge Intelligence (EI) integrates Edge Computing (EC) and Artificial Intelligence (AI) to push the capabilities of AI to the network edge for real-time, efficient and secure intelligent decision-making and computation.
Explicit Alignment and Many-to-many Entailment Based Reasoning for Conversational Machine Reading
Conversational Machine Reading (CMR) requires answering a user's initial question through multi-turn dialogue interactions based on a given document.
A Task-oriented Dialog Model with Task-progressive and Policy-aware Pre-training
A global policy consistency task is designed to capture the multi-turn dialog policy sequential relation, and an act-based contrastive learning task is designed to capture similarities among samples with the same dialog policy.
AKEM: Aligning Knowledge Base to Queries with Ensemble Model for Entity Recognition and Linking
This paper presents a novel approach to address the Entity Recognition and Linking Challenge at NLPCC 2015.
Whether you can locate or not? Interactive Referring Expression Generation
Referring Expression Generation (REG) aims to generate unambiguous Referring Expressions (REs) for objects in a visual scene, with a dual task of Referring Expression Comprehension (REC) to locate the referred object.
FATRER: Full-Attention Topic Regularizer for Accurate and Robust Conversational Emotion Recognition
This paper concentrates on the understanding of interlocutors' emotions evoked in conversational utterances.
Ranked #17 on
Emotion Recognition in Conversation
on IEMOCAP
Multimodal Recommendation Dialog with Subjective Preference: A New Challenge and Benchmark
Existing multimodal task-oriented dialog data fails to demonstrate the diverse expressions of user subjective preferences and recommendation acts in the real-life shopping scenario.
An Asynchronous Updating Reinforcement Learning Framework for Task-oriented Dialog System
The errors from DST might misguide the dialog policy, and the system action brings extra difficulties for the DST module.
CUR Transformer: A Convolutional Unbiased Regional Transformer for Image Denoising
Based on the prior that, for each pixel, its similar pixels are usually spatially close, our insights are that (1) we partition the image into non-overlapped windows and perform regional self-attention to reduce the search range of each pixel, and (2) we encourage pixels across different windows to communicate with each other.
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.
Towards Unifying Reference Expression Generation and Comprehension
Additionally, IRTF could generate pseudo input regions for the REC task to enable a uniform way for sharing the identical representation space across the REC and REG.
GR-GAN: Gradual Refinement Text-to-image Generation
We also introduce a new metric Cross-Model Distance (CMD) for simultaneously evaluating image quality and image-text consistency.
Question-Driven Graph Fusion Network For Visual Question Answering
It first models semantic, spatial, and implicit visual relations in images by three graph attention networks, then question information is utilized to guide the aggregation process of the three graphs, further, our QD-GFN adopts an object filtering mechanism to remove question-irrelevant objects contained in the image.
Co-VQA : Answering by Interactive Sub Question Sequence
Most existing approaches to Visual Question Answering (VQA) answer questions directly, however, people usually decompose a complex question into a sequence of simple sub questions and finally obtain the answer to the original question after answering the sub question sequence(SQS).
A Slot Is Not Built in One Utterance: Spoken Language Dialogs with Sub-Slots
We find some new linguistic phenomena and interactive manners in SSTOD which raise critical challenges of building dialog agents for the task.
Ranked #1 on
SSTOD
on SSD_NAME
Spot the Difference: A Cooperative Object-Referring Game in Non-Perfectly Co-Observable Scene
Visual dialog has witnessed great progress after introducing various vision-oriented goals into the conversation, especially such as GuessWhich and GuessWhat, where the only image is visible by either and both of the questioner and the answerer, respectively.
Deep Keyphrase Completion
Keyphrase provides accurate information of document content that is highly compact, concise, full of meanings, and widely used for discourse comprehension, organization, and text retrieval.
Topic-Aware Contrastive Learning for Abstractive Dialogue Summarization
To capture the various topic information of a conversation and outline salient facts for the captured topics, this work proposes two topic-aware contrastive learning objectives, namely coherence detection and sub-summary generation objectives, which are expected to implicitly model the topic change and handle information scattering challenges for the dialogue summarization task.
Ranked #3 on
Text Summarization
on SAMSum
Enhancing Visual Dialog Questioner with Entity-based Strategy Learning and Augmented Guesser
To enhance VD Questioner: 1) we propose a Related entity enhanced Questioner (ReeQ) that generates questions under the guidance of related entities and learns entity-based questioning strategy from human dialogs; 2) we propose an Augmented Guesser (AugG) that is strong and is optimized for the VD setting especially.
Dual Graph Convolutional Networks for Aspect-based Sentiment Analysis
To overcome these challenges, in this paper, we propose a dual graph convolutional networks (DualGCN) model that considers the complementarity of syntax structures and semantic correlations simultaneously.
Aspect-Based Sentiment Analysis
Aspect-Based Sentiment Analysis (ABSA)
+2
Multi-stage Pre-training over Simplified Multimodal Pre-training Models
Experimental results show that our method achieves comparable performance to the original LXMERT model in all downstream tasks, and even outperforms the original model in Image-Text Retrieval task.
Modeling Explicit Concerning States for Reinforcement Learning in Visual Dialogue
In Reinforcement Learning, it is crucial to represent states and assign rewards based on the action-caused transitions of states.
Converse, Focus and Guess -- Towards Multi-Document Driven Dialogue
We propose a novel task, Multi-Document Driven Dialogue (MD3), in which an agent can guess the target document that the user is interested in by leading a dialogue.
DialogueTRM: Exploring the Intra- and Inter-Modal Emotional Behaviors in the Conversation
Emotion Recognition in Conversations (ERC) is essential for building empathetic human-machine systems.
Weakly Supervised Real-time Image Cropping based on Aesthetic Distributions
In order to tackle this problem, a weakly supervised cropping frame- work is proposed, where the distribution dissimilarity between high quality images and cropped images is used to guide the coordinate predictor’s training and the ground truths of cropping windows are not required by the proposed method.
Answer-Driven Visual State Estimator for Goal-Oriented Visual Dialogue
In this paper, we propose an Answer-Driven Visual State Estimator (ADVSE) to impose the effects of different answers on visual states.
Label-Wise Document Pre-Training for Multi-Label Text Classification
A major challenge of multi-label text classification (MLTC) is to stimulatingly exploit possible label differences and label correlations.
Ranked #1 on
Multi-Label Text Classification
on AAPD
(Micro F1 metric)
Connecting Embeddings for Knowledge Graph Entity Typing
In this paper, we propose a novel approach for KG entity typing which is trained by jointly utilizing local typing knowledge from existing entity type assertions and global triple knowledge from KGs.
Cycle-CNN for Colorization towards Real Monochrome-Color Camera Systems
We present a new CNN model, named cycle CNN, which can directly use the real data from monochrome-color camera systems for training.
Guessing State Tracking for Visual Dialogue
This paper proposes a guessing state for the Guesser, and regards guess as a process with change of guessing state through a dialogue.
Dual-CNN: A Convolutional language decoder for paragraph image captioning
Abstract The task of paragraph image captioning aims to generate a coherent paragraph describing a given image.
Visual Dialogue State Tracking for Question Generation
A visual dialogue state is defined as the distribution on objects in the image as well as representations of objects.
MrMep: Joint Extraction of Multiple Relations and Multiple Entity Pairs Based on Triplet Attention
This paper focuses on how to extract multiple relational facts from unstructured text.
Cascaded LSTMs based Deep Reinforcement Learning for Goal-driven Dialogue
Dialogue embeddings are learned by a LSTM at the middle of the network, and updated by the feeding of all turn embeddings.
Learning a Deep Convolutional Network for Colorization in Monochrome-Color Dual-Lens System
To get high-quality color images, it is desired to colorize the gray image with the color image as reference.
Doubly Robust Joint Learning for Recommendation on Data Missing Not at Random
In recommender systems, usually the ratings of a user to most items are missing and a critical problem is that the missing ratings are often missing not at random (MNAR) in reality.
Deep Reason: A Strong Baseline for Real-World Visual Reasoning
This paper presents a strong baseline for real-world visual reasoning (GQA), which achieves 60. 93% in GQA 2019 challenge and won the sixth place.
KDGAN: Knowledge Distillation with Generative Adversarial Networks
An alternative method is to adversarially train the classifier against a discriminator in a two-player game akin to generative adversarial networks (GAN), which can ensure the classifier to learn the true data distribution at the equilibrium of this game.
Chain of Reasoning for Visual Question Answering
A chain of reasoning (CoR) is constructed for supporting multi-step and dynamic reasoning on changed relations and objects.
Finding More Relevance: Propagating Similarity on Markov Random Field for Image Retrieval
To effectively retrieve objects from large corpus with high accuracy is a challenge task.
Constructing Hierarchical Image-tags Bimodal Representations for Word Tags Alternative Choice
This paper describes our solution to the multi-modal learning challenge of ICML.
Challenges in Representation Learning: A report on three machine learning contests
The ICML 2013 Workshop on Challenges in Representation Learning focused on three challenges: the black box learning challenge, the facial expression recognition challenge, and the multimodal learning challenge.
Ranked #12 on
Facial Expression Recognition (FER)
on FER2013
