Amir Saeidi
Amir Saeidi has 3 papers in our library, in 2024–2026, most of them on Language models & pretraining, Question answering, Reasoning; often with Chitta Baral, Divij Handa, Md Nayem Uddin.
OpenAlex · h-index 2 · 13 works · 12 citations OpenAlex, 2026-10-14
📄 3 works in our library · 🔗 Cited 25 times in our library · ⭐ Paper Stars ranking: #8501
Affiliations
Fields, topics and concepts
📚 Shelves 5The field of science this work belongs to (OpenAlex fields).Arts and Humanities · 3 worksComputer Science · 3 worksArtificial Intelligence · 3 worksLanguage and Linguistics · 3 worksComputer Vision and Pattern Recognition · 1 work
🧭 Topics 4Research subjects and languages the work is about.Language models & pretraining · 3 worksQuestion answering · 1 workBias, fairness & safety · 1 workReasoning · 1 work
Works by year
2020s
Papers
- When "Competency" in Reasoning Opens the Door to Vulnerability: Jailbreaking LLMs via Novel Complex Ciphers (2024 · 15 citations)
Safety training for LLMs usually covers harmful requests in natural language or in well-known encodings such as Base64. This work argues that this leaves a gap: stronger reasoning lets models decode ciphers invented on the spot, and defenders cannot anticipate such ciphers in alignment data. - UnSeenTimeQA: Time-Sensitive Question-Answering Beyond LLMs' Memorization (2025 · 14 citations)
Benchmarks for time-sensitive question answering (TSQA), such as TimeQA, TempReason and MenatQA, are built from real-world Wikidata/Wikipedia facts. - FAMA: Failure-Aware Meta-Agentic Framework for Open-Source LLMs in Interactive Tool Use Environments (2026)
LLM-driven agents in multi-turn customer-service tool-use settings often fail because early wrong decisions compound over the conversation.
Co-authors here
- Chitta Baral ×3
- Divij Handa ×2
- Md Nayem Uddin ×2
- Ali Payani
- Eduardo Blanco
- Gaowen Liu
- Jayanth Srinivasa
- Shrinidhi Kumbhar
Venues
- Annual Meeting of the Association for Computational Linguistics (ACL): ACL 2025
- Findings of the Association for Computational Linguistics: Findings of the Association for Computational Linguistics 2026
Cited by
Updated
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