Cover Image

Adversarial Attacks against Neural Ranking Models via In-Context Learning

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bigdeli, Amin, Arabzadeh, Negar, Bagheri, Ebrahim, Clarke, Charles L. A.
Format:	Preprint
Published:	2025
Subjects:	Information Retrieval Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

EMPRA: Embedding Perturbation Rank Attack against Neural Ranking Models
by: Bigdeli, Amin, et al.
Published: (2024)

ReFormeR: Learning and Applying Explicit Query Reformulation Patterns
by: Bigdeli, Amin, et al.
Published: (2026)

Led to Mislead: Adversarial Content Injection for Attacks on Neural Ranking Models
by: Bigdeli, Amin, et al.
Published: (2026)

QueryGym: A Toolkit for Reproducible LLM-Based Query Reformulation
by: Bigdeli, Amin, et al.
Published: (2025)

A Reproducibility Study of LLM-Based Query Reformulation
by: Bigdeli, Amin, et al.
Published: (2026)

Adapting Standard Retrieval Benchmarks to Evaluate Generated Answers
by: Arabzadeh, Negar, et al.
Published: (2024)

Benchmarking LLM-based Relevance Judgment Methods
by: Arabzadeh, Negar, et al.
Published: (2025)

A Human-AI Comparative Analysis of Prompt Sensitivity in LLM-Based Relevance Judgment
by: Arabzadeh, Negar, et al.
Published: (2025)

exHarmony: Authorship and Citations for Benchmarking the Reviewer Assignment Problem
by: Ebrahimi, Sajad, et al.
Published: (2025)

Evaluating the Robustness of Retrieval-Augmented Generation to Adversarial Evidence in the Health Domain
by: Amirshahi, Shakiba, et al.
Published: (2025)

Benchmarking Prompt Sensitivity in Large Language Models
by: Razavi, Amirhossein, et al.
Published: (2025)

Peerispect: Claim Verification in Scientific Peer Reviews
by: Ghorbanpour, Ali, et al.
Published: (2026)

Fréchet Distance for Offline Evaluation of Information Retrieval Systems with Sparse Labels
by: Arabzadeh, Negar, et al.
Published: (2024)

A Comparison of Methods for Evaluating Generative IR
by: Arabzadeh, Negar, et al.
Published: (2024)

Can QPP Choose the Right Query Variant? Evaluating Query Variant Selection for RAG Pipelines
by: Arabzadeh, Negar, et al.
Published: (2026)

RAG over Thinking Traces Can Improve Reasoning Tasks
by: Arabzadeh, Negar, et al.
Published: (2026)

Ranked List Truncation for Large Language Model-based Re-Ranking
by: Meng, Chuan, et al.
Published: (2024)

Generative Information Retrieval Evaluation
by: Alaofi, Marwah, et al.
Published: (2024)

One Word is Enough: Minimal Adversarial Perturbations for Neural Text Ranking
by: Karmakar, Tanmay, et al.
Published: (2026)

Sliding Windows Are Not the End: Exploring Full Ranking with Long-Context Large Language Models
by: Liu, Wenhan, et al.
Published: (2024)

ProRank: Prompt Warmup via Reinforcement Learning for Small Language Models Reranking
by: Li, Xianming, et al.
Published: (2025)

Offline Evaluation of Set-Based Text-to-Image Generation
by: Arabzadeh, Negar, et al.
Published: (2024)

ConExion: Concept Extraction with Large Language Models
by: Norouzi, Ebrahim, et al.
Published: (2025)

Query Performance Prediction using Relevance Judgments Generated by Large Language Models
by: Meng, Chuan, et al.
Published: (2024)

LTRR: Learning To Rank Retrievers for LLMs
by: Kim, To Eun, et al.
Published: (2025)

Learning to Retrieve In-Context Examples for Large Language Models
by: Wang, Liang, et al.
Published: (2023)

Ambiguity-Aware In-Context Learning with Large Language Models
by: Gao, Lingyu, et al.
Published: (2023)

Learning to Rank for Multiple Retrieval-Augmented Models through Iterative Utility Maximization
by: Salemi, Alireza, et al.
Published: (2024)

DemoRank: Selecting Effective Demonstrations for Large Language Models in Ranking Task
by: Liu, Wenhan, et al.
Published: (2024)

Rank-R1: Enhancing Reasoning in LLM-based Document Rerankers via Reinforcement Learning
by: Zhuang, Shengyao, et al.
Published: (2025)

The Role of Vocabularies in Learning Sparse Representations for Ranking
by: Kim, Hiun, et al.
Published: (2025)

CoRanking: Collaborative Ranking with Small and Large Ranking Agents
by: Liu, Wenhan, et al.
Published: (2025)

OpenRAG: Optimizing RAG End-to-End via In-Context Retrieval Learning
by: Zhou, Jiawei, et al.
Published: (2025)

Re-Ranking Step by Step: Investigating Pre-Filtering for Re-Ranking with Large Language Models
by: Nouriinanloo, Baharan, et al.
Published: (2024)

TourRank: Utilizing Large Language Models for Documents Ranking with a Tournament-Inspired Strategy
by: Chen, Yiqun, et al.
Published: (2024)

PASH at TREC 2021 Deep Learning Track: Generative Enhanced Model for Multi-stage Ranking
by: Qiao, Yixuan, et al.
Published: (2022)

REGENT: Relevance-Guided Attention for Entity-Aware Multi-Vector Neural Re-Ranking
by: Chatterjee, Shubham
Published: (2025)

RobustMask: Certified Robustness against Adversarial Neural Ranking Attack via Randomized Masking
by: Liu, Jiawei, et al.
Published: (2025)

A Trio Neural Model for Dynamic Entity Relatedness Ranking
by: Nguyen, Tu, et al.
Published: (2018)

Optimal Dataset Size for Recommender Systems: Evaluating Algorithms' Performance via Downsampling
by: Arabzadeh, Ardalan
Published: (2025)