Ibrahim Abdelaziz
Ibrahim Abdelaziz has 2 papers in our library, in 2021–2025, most of them on Language models & pretraining, Question answering, Evaluation & benchmarks; often with Alfio Gliozzo, Dinesh Garg, Kinjal Basu.
OpenAlex · ORCID · Wikidata · h-index 20 · 94 works · 1,612 citations OpenAlex, 2026-10-14
📄 2 works in our library · 🔗 Cited 117 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #6104
Affiliations
Fields, topics and concepts
📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 2 worksComputer Science · 2 worksArtificial Intelligence · 2 worksLanguage and Linguistics · 2 worksInformation Systems · 1 work
🧭 Topics 5Research subjects and languages the work is about.Knowledge graphs & ontologies · 1 workQuestion answering · 1 workSemantic parsing & meaning representation · 1 workEvaluation & benchmarks · 1 workLanguage models & pretraining · 1 work
💡 Concepts 1Key ideas and methods explained on our concept pages.Semantics · 1 work
Works by year
2020s
Papers
- Leveraging Abstract Meaning Representation for Knowledge Base Question Answering (2021 · 141 citations)
The paper addresses knowledge base question answering (KBQA). Here a system must convert a natural-language question into a structured query, for example SPARQL, and find the answer among the facts in the knowledge base. The main challenges are complex multi-hop questions, the need for logical reasoning, and the lack… - NESTFUL: A Benchmark for Evaluating LLMs on Nested Sequences of API Calls (2025 · 16 citations)
Benchmarks for LLM tool calling usually treat an API sequence as a set of independent calls. Many real tasks instead need nesting, where one call's result becomes an argument to a later call. NESTFUL (IBM Research) targets this gap with more than 1,800 nested sequences built from MathQA and StarCoder2-Instruct.
All works
- Leveraging Abstract Meaning Representation for Knowledge Base Question AnsweringFindings of the Association for Computational LinguisticsPavan Kapanipathi, Ibrahim Abdelaziz, Srinivas Ravishankar, et al.2021 · 141 citations
- Granite Code Models: A Family of Open Foundation Models for Code Intelligence ↗arXiv:2405.04324 · no summary yetMayank Mishra et al.2024 · 54 citations
- NESTFUL: A Benchmark for Evaluating LLMs on Nested Sequences of API CallsConference on Empirical Methods in Natural Language Processing (EMNLP)Kinjal Basu, Ibrahim Abdelaziz, Kiran Kate, et al.2025 · 16 citations
Co-authors here
- Alfio Gliozzo
- Dinesh Garg
- Kinjal Basu
- Luis Lastras
- Ramón Fernandez Astudillo
- Sadhana Kumaravel
- Salim Roukos
- Xin Wang
Venues
- Conference on Empirical Methods in Natural Language Processing (EMNLP): EMNLP 2025
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2021
Cited by
Updated
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