◍wovepaper
SearchResearchersInstitutions
Sign in
researcher

Yashar Moshfeghi

University of Strathclyde

19 papers hereh-index 252k citations126 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author1
  • middle author4
  • last author14

Across the 19 of 19 papers where every author was matched, so the position is known.

fields
  • cs.LG5
  • cs.AI4
  • cs.IR4
  • cs.CL2
  • cs.CY1
  • cs.HC1
affiliations
  • University of Strathclyde
same name
  • Yashar Moshfeghi — 4 papers, h 1

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20222026
most citedELASTIC: Numerical Reasoning with Adaptive Symbolic Compiler

9 citations · 25 across the 19 of their papers we have counts for

collaborators
Showing cs.IRShow all

4 papers · 1 filter

cs.IR2025★ 1 cited

Brain-Machine Interfaces & Information Retrieval Challenges and Opportunities

Yashar Moshfeghi, Niall McGuire

The fundamental goal of Information Retrieval (IR) systems lies in their capacity to effectively satisfy human information needs - a challenge that encompasses not just the technic…

cs.IR2024★ 1 cited

Towards Brain Passage Retrieval -- An Investigation of EEG Query Representations

Niall McGuire, Yashar Moshfeghi

Information Retrieval (IR) systems primarily rely on users' ability to translate their internal information needs into (text) queries. However, this translation process is often un…

cs.IR2024

Prediction of the Realisation of an Information Need: An EEG Study

Niall McGuire, Dr Yashar Moshfeghi

One of the foundational goals of Information Retrieval (IR) is to satisfy searchers' Information Needs (IN). Understanding how INs physically manifest has long been a complex and e…

cs.IR2023★ 9 cited

Why People Skip Music? On Predicting Music Skips using Deep Reinforcement Learning

Francesco Meggetto, Crawford Revie, John Levine +1

Music recommender systems are an integral part of our daily life. Recent research has seen a significant effort around black-box recommender based approaches such as Deep Reinforce…

◍wovepaper

Papers, researchers and institutions, woven together.

Explore
  • Search
  • Researchers
  • Institutions
Account
  • Library
  • Chat
Data
  • arXiv.org
  • Semantic Scholar
  • OpenAlex
  • Latest RSS
AboutContactPrivacyDevelopersllms.txtopenapi.json
Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.