Argument Retrieval

7 papers with code • 2 benchmarks • 3 datasets

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Most implemented papers

BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models

UKPLab/beir 17 Apr 2021

To address this, and to facilitate researchers to broadly evaluate the effectiveness of their models, we introduce Benchmarking-IR (BEIR), a robust and heterogeneous evaluation benchmark for information retrieval.

Evaluating Fairness in Argument Retrieval

sachinpc1993/fair-arguments 23 Aug 2021

In this work, we analyze a range of non-stochastic fairness-aware ranking and diversity metrics to evaluate the extent to which argument stances are fairly exposed in argument retrieval systems.

Fine-Grained Argument Unit Recognition and Classification

trtm/AURC 22 Apr 2019

In this work, we argue that the task should be performed on a more fine-grained level of sequence labeling.

Diversity Aware Relevance Learning for Argument Search

fromm-m/ecir2021-am-search 4 Nov 2020

In this work, we focus on the problem of retrieving relevant arguments for a query claim covering diverse aspects.

SGPT: GPT Sentence Embeddings for Semantic Search

muennighoff/sgpt 17 Feb 2022

To this end, we propose SGPT to use decoders for sentence embeddings and semantic search via prompting or fine-tuning.

No Parameter Left Behind: How Distillation and Model Size Affect Zero-Shot Retrieval

guilhermemr04/scaling-zero-shot-retrieval 6 Jun 2022

This has made distilled and dense models, due to latency constraints, the go-to choice for deployment in real-world retrieval applications.

Incorporating Relevance Feedback for Information-Seeking Retrieval using Few-Shot Document Re-Ranking

ukplab/incorporating-relevance 19 Oct 2022

Pairing a lexical retriever with a neural re-ranking model has set state-of-the-art performance on large-scale information retrieval datasets.