Papers Argument Retrieval
“Argument Retrieval” 태그가 달린 논문 14편 · 필터 해제
Overview of PerpectiveArg2024: The First Shared Task on Perspective Argument Retrieval
Argument retrieval is the task of finding relevant arguments for a given query. While existing approaches rely solely on the semantic alignment of queries and arguments, this first shared task on perspective argument ret…
Argument RetrievalRetrievalSystematic Evaluation of Neural Retrieval Models on the Touché 2020 Argument Retrieval Subset of BEIR
The zero-shot effectiveness of neural retrieval models is often evaluated on the BEIR benchmark -- a combination of different IR evaluation datasets. Interestingly, previous studies found that particularly on the BEIR su…
Argument RetrievalDenoisingRetrievalRetrieving Comparative Arguments using Ensemble Methods and Neural Information Retrieval
In this paper, we present a submission to the Touche lab's Task 2 on Argument Retrieval for Comparative Questions. Our team Katana supplies several approaches based on decision tree ensembles algorithms to rank comparati…
Argument RetrievalInformation RetrievalLanguage ModellingRetrieval+1Revisiting the Role of Similarity and Dissimilarity in Best Counter Argument Retrieval
This paper studies the task of best counter-argument retrieval given an input argument. Following the definition that the best counter-argument addresses the same aspects as the input argument while having the opposite s…
Argument RetrievalLearning-To-RankRetrievalMulti-Vector Retrieval as Sparse Alignment
Multi-vector retrieval models improve over single-vector dual encoders on many information retrieval tasks. In this paper, we cast the multi-vector retrieval problem as sparse alignment between query and document tokens.…
Argument RetrievalInformation RetrievalRetrievalIncorporating 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+2No Parameter Left Behind: How Distillation and Model Size Affect Zero-Shot Retrieval
Recent work has shown that small distilled language models are strong competitors to models that are orders of magnitude larger and slower in a wide range of information retrieval tasks. This has made distilled and dense…
Argument RetrievalBiomedical Information RetrievalCitation PredictionDuplicate-Question Retrieval+7SGPT: GPT Sentence Embeddings for Semantic Search
Decoder transformers have continued increasing in scale reaching hundreds of billions of parameters. Due to their scale the same decoder sets state-of-the-art results on various language tasks via prompting or fine-tunin…
Argument RetrievalBiomedical Information RetrievalCitation PredictionDecoder+11Image Retrieval for Arguments Using Stance-Aware Query Expansion
Many forms of argumentation employ images as persuasive means, but research in argument mining has been focused on verbal argumentation so far. This paper shows how to integrate images into argument mining research, spec…
Argument MiningArgument RetrievalImage RetrievalRetrievalEvaluating Fairness in Argument Retrieval
Existing commercial search engines often struggle to represent different perspectives of a search query. Argument retrieval systems address this limitation of search engines and provide both positive (PRO) and negative (…
Argument RetrievalDiversityFairnessRetrievalBEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
Existing neural information retrieval (IR) models have often been studied in homogeneous and narrow settings, which has considerably limited insights into their out-of-distribution (OOD) generalization capabilities. To a…
Argument RetrievalBenchmarkingBiomedical Information RetrievalCitation Prediction+11Diversity Aware Relevance Learning for Argument Search
In this work, we focus on the problem of retrieving relevant arguments for a query claim covering diverse aspects. State-of-the-art methods rely on explicit mappings between claims and premises, and thus are unable to ut…
Argument RetrievalClusteringDiversityRetrievalFine-Grained Argument Unit Recognition and Classification
Prior work has commonly defined argument retrieval from heterogeneous document collections as a sentence-level classification task. Consequently, argument retrieval suffers both from low recall and from sentence segmenta…
Argument MiningArgument RetrievalClassificationGeneral Classification+3ArgumenText: Searching for Arguments in Heterogeneous Sources
Argument mining is a core technology for enabling argument search in large corpora. However, most current approaches fall short when applied to heterogeneous texts. In this paper, we present an argument retrieval system …
Argument MiningArgument RetrievalInformation RetrievalQuestion Answering+2