Search Results for author:
Found 16 papers, 7 papers with code
Improving Multiple Documents Grounded Goal-Oriented Dialog Systems via Diverse Knowledge Enhanced Pretrained Language Model
In this paper, we mainly discuss about our submission to MultiDoc2Dial task, which aims to model the goal-oriented dialogues grounded in multiple documents.
Learning to Select Question-Relevant Relations for Visual Question Answering
Previous existing visual question answering (VQA) systems commonly use graph neural networks(GNNs) to extract visual relationships such as semantic relations or spatial relations.
ViLBERTScore: Evaluating Image Caption Using Vision-and-Language BERT
In this paper, we propose an evaluation metric for image captioning systems using both image and text information.
Asking Clarification Questions to Handle Ambiguity in Open-Domain QA
We first present CAMBIGNQ, a dataset consisting of 5, 654 ambiguous questions, each with relevant passages, possible answers, and a clarification question.
Critic-Guided Decoding for Controlled Text Generation
In this work, we propose a novel critic decoding method for controlled language generation (CriticControl) that combines the strengths of reinforcement learning and weighted decoding.
Task-specific Compression for Multi-task Language Models using Attribution-based Pruning
However, these language models utilize an unnecessarily large number of model parameters, even when used only for a specific task.
Masked Summarization to Generate Factually Inconsistent Summaries for Improved Factual Consistency Checking
To this end, the latest approach is to train a factual consistency classifier on factually consistent and inconsistent summaries.
Factual Error Correction for Abstractive Summaries Using Entity Retrieval
In this paper, we propose an efficient factual error correction system RFEC based on entities retrieval post-editing process.
CrossAug: A Contrastive Data Augmentation Method for Debiasing Fact Verification Models
Specifically, we employ a two-stage augmentation pipeline to generate new claims and evidences from existing samples.
UMIC: An Unreferenced Metric for Image Captioning via Contrastive Learning
Also, we observe critical problems of the previous benchmark dataset (i. e., human annotations) on image captioning metric, and introduce a new collection of human annotations on the generated captions.
KPQA: A Metric for Generative Question Answering Using Keyphrase Weights
To evaluate our metric, we create high-quality human judgments of correctness on two GenQA datasets.
DSTC8-AVSD: Multimodal Semantic Transformer Network with Retrieval Style Word Generator
Audio Visual Scene-aware Dialog (AVSD) is the task of generating a response for a question with a given scene, video, audio, and the history of previous turns in the dialog.
Attentive Modality Hopping Mechanism for Speech Emotion Recognition
In this work, we explore the impact of visual modality in addition to speech and text for improving the accuracy of the emotion detection system.
Improving Neural Question Generation using Answer Separation
Previous NQG models suffer from a problem that a significant proportion of the generated questions include words in the question target, resulting in the generation of unintended questions.
AttnConvnet at SemEval-2018 Task 1: Attention-based Convolutional Neural Networks for Multi-label Emotion Classification
In this paper, we propose an attention-based classifier that predicts multiple emotions of a given sentence.
