Papers Re-Ranking
“Re-Ranking” 태그가 달린 논문 743편 · 필터 해제
A Benchmark of Video-Based Clothes-Changing Person Re-Identification
Person re-identification (Re-ID) is a classical computer vision task and has achieved great progress so far. Recently, long-term Re-ID with clothes-changing has attracted increasing attention. However, existing methods m…
Clothes Changing Person Re-IdentificationPerson Re-IdentificationRe-RankingVideo-Based Person Re-IdentificationRanking Aggregation with Interactive Feedback for Collaborative Person Re-identification
Person re-identification (re-ID) aims to retrieve the same person from a group of networking cameras. Ranking aggregation (RA), a method to aggregates multiple ranking results, can further improve the retrieval accuracy …
Person Re-IdentificationRe-RankingRetrievalRobust Unstructured Knowledge Access in Conversational Dialogue with ASR Errors
Performance of spoken language understanding (SLU) can be degraded with automatic speech recognition (ASR) errors. We propose a novel approach to improve SLU robustness by randomly corrupting clean training text with an …
Automatic Speech RecognitionAutomatic Speech Recognition (ASR)DecoderRe-Ranking+3Noisy Channel for Automatic Text Simplification
In this paper we present a simple re-ranking method for Automatic Sentence Simplification based on the noisy channel scheme. Instead of directly computing the best simplification given a complex text, the re-ranking meth…
Language ModelingLanguage ModellingRe-RankingSentence+1Improving abstractive summarization with energy-based re-ranking
Current abstractive summarization systems present important weaknesses which prevent their deployment in real-world applications, such as the omission of relevant information and the generation of factual inconsistencies…
Abstractive Text SummarizationRe-RankingMetric-guided Distillation: Distilling Knowledge from the Metric to Ranker and Retriever for Generative Commonsense Reasoning
Commonsense generation aims to generate a realistic sentence describing a daily scene under the given concepts, which is very challenging, since it requires models to have relational reasoning and compositional generaliz…
Relational ReasoningRe-RankingSentenceAutomatic Check-Out via Prototype-based Classifier Learning from Single-Product Exemplars
Automatic Check-Out (ACO) aims to accurately predict the presence and count of each category of products in check-out images, where a major challenge is the significant domain gap between training data (single-product ex…
Re-RankingIncorporating Relevance Feedback for Information-Seeking Retrieval using Few-Shot Document Re-Ranking
Pairing a lexical retriever with a neural re-ranking model has set state-of-the-art performance on large-scale information retrieval datasets. This pipeline covers scenarios like question answering or navigational querie…
Argument RetrievalInformation RetrievalMeta-LearningQuestion Answering+2Towards Summary Candidates Fusion
Sequence-to-sequence deep neural models fine-tuned for abstractive summarization can achieve great performance on datasets with enough human annotations. Yet, it has been shown that they have not reached their full poten…
Abstractive Text SummarizationRe-RankingRetrieval Augmentation for T5 Re-ranker using External Sources
Retrieval augmentation has shown promising improvements in different tasks. However, whether such augmentation can assist a large language model based re-ranker remains unclear. We investigate how to augment T5-based re-…
Language ModelingLanguage ModellingLarge Language ModelRe-Ranking+1Spectral Geometric Verification: Re-Ranking Point Cloud Retrieval for Metric Localization
In large-scale metric localization, an incorrect result during retrieval will lead to an incorrect pose estimate or loop closure. Re-ranking methods propose to take into account all the top retrieval candidates and re-or…
Point Cloud RegistrationPoint Cloud RetrievalPose EstimationRe-Ranking+1Pyramidal Transformer with Conv-Patchify for Person Re-identification
The robust and discriminative feature extraction is the key component in person re-identification (Re-ID). The major weakness ofconventional convolution neural network (CNN) based methods is that they cannot extract long…
Person Re-IdentificationRe-RankingTranslationSpecialized Re-Ranking: A Novel Retrieval-Verification Framework for Cloth Changing Person Re-Identification
Cloth changing person re-identification(Re-ID) can work under more complicated scenarios with higher security than normal Re-ID and biometric techniques and is therefore extremely valuable in applications. Meanwhile, hig…
Cloth-Changing Person Re-IdentificationPerson Re-IdentificationRe-RankingRetrievalTextGraphs-16 Natural Language Premise Selection Task: Zero-Shot Premise Selection with Prompting Generative Language Models
Automated theorem proving can benefit a lot from methods employed in natural language processing, knowledge graphs and information retrieval: this non-trivial task combines formal languages understanding, reasoning, simi…
Automated Theorem ProvingInformation RetrievalKnowledge GraphsNatural Language Understanding+5COLO: A Contrastive Learning based Re-ranking Framework for One-Stage Summarization
Traditional training paradigms for extractive and abstractive summarization systems always only use token-level or sentence-level training objectives. However, the output summary is always evaluated from summary-level wh…
Abstractive Text SummarizationContrastive LearningGPURe-Ranking+1FiD-Light: Efficient and Effective Retrieval-Augmented Text Generation
Retrieval-augmented generation models offer many benefits over standalone language models: besides a textual answer to a given query they provide provenance items retrieved from an updateable knowledge base. However, the…
DecoderOpen-Domain Question AnsweringRe-RankingRetrieval+2T5QL: Taming language models for SQL generation
Automatic SQL generation has been an active research area, aiming at streamlining the access to databases by writing natural language with the given intent instead of writing SQL. Current SOTA methods for semantic parsin…
Code GenerationRe-RankingSemantic ParsingText-To-SQL+1Automatic Label Sequence Generation for Prompting Sequence-to-sequence Models
Prompting, which casts downstream applications as language modeling tasks, has shown to be sample efficient compared to standard fine-tuning with pre-trained models. However, one pitfall of prompting is the need of manua…
Few-Shot LearningLanguage ModelingLanguage ModellingRe-RankingBelief Revision based Caption Re-ranker with Visual Semantic Information
In this work, we focus on improving the captions generated by image-caption generation systems. We propose a novel re-ranking approach that leverages visual-semantic measures to identify the ideal caption that maximally …
Caption GenerationImage CaptioningNatural Language UnderstandingNatural Language Visual Grounding+2Multilingual Transformer Language Model for Speech Recognition in Low-resource Languages
It is challenging to train and deploy Transformer LMs for hybrid speech recognition 2nd pass re-ranking in low-resource languages due to (1) data scarcity in low-resource languages, (2) expensive computing costs for trai…
Language ModelingLanguage ModellingRe-Rankingspeech-recognition+1