Idan Szpektor
Artificial Intelligence · 2004–2025
A researcher in the Science corpus: 13 papers; trusts 181 researchers and is trusted by 46 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 244 citations into it; #9,516 of 35,345 by trust here, #11,490 by citations
- Natural Language Processing — 158 citations into it; #1,072 of 5,688 by trust here, #904 by citations
- Computer Vision and Pattern Recognition — 106 citations into it
- Evaluation & Benchmarks — 94 citations into it; #2,197 of 3,147 by trust here, #835 by citations
- Information Retrieval & Search — 12 citations into it
- Representation & Self-Supervised Learning — 10 citations into it; #2,585 of 3,145 by trust here, #2,488 by citations
- Information Systems — 9 citations into it; #1,849 of 8,771 by trust here, #3,198 by citations
- Computational Linguistics & Semantics — 5 citations into it
Whom Idan Szpektor trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Dekang Lin
- Ido Dagan
- Julie Weeds
- Deepak Ravichandran
- Ellen Riloff
- Maayan Zhitomirsky-Geffet
- Kaiming He
- Geoffrey E. Hinton
- Yoshua Bengio
- Diederik P. Kingma
Who trusts Idan Szpektor overall
- Ido Dagan
- Jonathan Berant
- Ion Androutsopoulos
- Roy Bar-Haim
- Prodromos Malakasiotis
- Naomi Zeichner
- Lili Kotlerman
- Asher Stern
- Jacob Goldberger
- Bernardo Magnini
Papers from Idan Szpektor's perspective
Ordered by how strongly the researchers Idan Szpektor trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Attention is All you Need (Neural Information Processing Systems)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- ImageNet Large Scale Visual Recognition Challenge
- Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
Their papers
- All You May Need for VQA are Image Captions (2022) — 93 citations
- TRUE: Re-evaluating Factual Consistency Evaluation (2022) — 372 citations
- Directional distributional similarity for lexical inference (2010) — 244 citations
- Learning Entailment Rules for Unary Templates (2008) — 123 citations
- Dynamic Planning in Open-Ended Dialogue using Reinforcement Learning (2022) — 13 citations
- Semantic Inference at the Lexical-Syntactic Level for Textual Entailment Recognition (2007) — 41 citations
- Gemini 2.5: Pushing the Frontier with Advanced Reasoning, Multimodality, Long Context, and Next Generation Agentic Capabilities (2025) — 3,609 citations
- Gemma 3 Technical Report (2025) — 1,621 citations
- Q^{2}: Evaluating Factual Consistency in Knowledge-Grounded Dialogues via Question Generation and Question Answering (2021) — 167 citations
- Churn prediction in new users of Yahoo! answers (2012) — 122 citations
- The Second PASCAL Recognising Textual Entailment Challenge (2006)
- Investigating a Generic Paraphrase-Based Approach for Relation Extraction (2006) — 120 citations
- Scaling Web-based Acquisition of Entailment Relations (2004) — 211 citations