activity
20182026
most citedHybrid Forest: A Concept Drift Aware Data Stream Mining Algorithm

9 citations · 9 across the 6 of their papers we have counts for

collaborators

10 papers

cs.IR2026

Seek: Self-Evaluative Exploration for Knowledge Retrieval

Amin Bigdeli, Radin Hamidi Rad, Negar Arabzadeh +4

LLM-based retrievers and rerankers have advanced passage ranking, yet both paradigms interact with the corpus in a single pass and commit to the resulting candidate set, leaving re…

cs.IR2026

Route Me If You Can: A Benchmark for Query Reformulation Selection

Hai Son Le, Negar Arabzadeh, Amin Bigdeli +4

LLM-based query reformulation can improve retrieval, but no single reformulation strategy is consistently optimal across queries, domains, retrievers, or model backbones. This crea…

cs.AI2026

Question's Gambit: The First Move Matters in Agentic Deep Search

Radin Hamidi Rad, Amin Bigdeli, Negar Arabzadeh +4

Deep research agents answer complex questions through iterative loops of searching, reading, and reasoning. Recent work on reasoning-intensive benchmarks such as BrowseComp-Plus sh…

cs.IR2026

ADORE: Iterative Query Expansion with Retrieval-Grounded Relevance Feedback

Amin Bigdeli, Negar Arabzadeh, Radin Hamidi Rad +3

LLM-based query expansion improves retrieval by enriching the original query with additional context. Yet most methods remain generation-driven, producing plausible pseudo-document…

cs.IR2026

Led to Mislead: Adversarial Content Injection for Attacks on Neural Ranking Models

Amin Bigdeli, Amir Khosrojerdi, Radin Hamidi Rad +3

Neural Ranking Models (NRMs) are central to modern information retrieval but remain highly vulnerable to adversarial manipulation. Existing attacks often rely on heuristics or surr…

cs.IR2026

A Reproducibility Study of LLM-Based Query Reformulation

Amin Bigdeli, Radin Hamidi Rad, Hai Son Le +4

Large Language Models (LLMs) are now widely used for query reformulation and expansion in Information Retrieval, with many studies reporting substantial effectiveness gains. Howeve…

cs.AI2026

Adaptive Prompt Embedding Optimization for LLM Jailbreaking

Miles Q. Li, Benjamin C. M. Fung, Boyang Li +2

Existing white-box jailbreak attacks against aligned LLMs typically append discrete adversarial suffixes to the user prompt, which visibly alters the prompt and operates in a combi…

cs.IR2025

QueryGym: A Toolkit for Reproducible LLM-Based Query Reformulation

Amin Bigdeli, Radin Hamidi Rad, Mert Incesu +3

We present QueryGym, a lightweight, extensible Python toolkit that supports large language model (LLM)-based query reformulation. This is an important tool development since recent…

cs.LG2019★ 9 cited

Hybrid Forest: A Concept Drift Aware Data Stream Mining Algorithm

Radin Hamidi Rad, Maryam Amir Haeri

Nowadays with a growing number of online controlling systems in the organization and also a high demand of monitoring and stats facilities that uses data streams to log and control…

cs.IR2018

A Fuzzy Community-Based Recommender System Using PageRank

Maliheh Goliforoushani, Radin Hamidi Rad, Maryam Amir Haeri

Recommendation systems are widely used by different user service providers specially those who have interactions with the large community of users. This paper introduces a recommen…