Alon Jacovi
17 papers · 2018–2025 · 7 conferences · across top CS/AI conferences
Achievements
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๐ Academic Marathon (7) ๐งญ Keyword Pioneer ๐ Interdisciplinary Bridge ๐ Conference Polyglot (6) ๐ Cross-Pollinator (12)
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Cross-Pollinator
(12)
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Renaissance Researcher
(5)
๐บ๏ธ
Taxonomy Completionist
(38)
๐งฌ
Topic Evolution
๐ฅ
Mega-Team
(28)
๐๏ธ
Keyword Collector
(82)
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Century Club
(16)
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Trend Setter
โ
The Questioner
(2)
Conferences
ACL (6)
EMNLP (6)
AACL (1)
EACL (1)
ICLR (1)
IJCNLP (1)
NIPS (1)
Top co-authors
Research topics
Keywords
question answering
(4)
in-context learning
(3)
few-shot learning
(3)
information retrieval
(2)
text classification
(2)
feature attribution
(2)
language model
(2)
data contamination
(2)
large language model
(2)
model interpretability
(2)
data augmentation
(1)
model evaluation
(1)
prompt engineering
(1)
model robustness
(1)
concept-based explanation
(1)
information extraction
(1)
benchmark dataset
(1)
convolutional neural network
(1)
interpretability evaluation
(1)
relation extraction
(1)
Papers
ConSim: Measuring Concept-Based Explanationsโ Effectiveness with Automated Simulatability
ACL 2025
DoubleDipper: Recycling Contexts for Efficient and Attributed In-Context Learning
AACL 2025
DoubleDipper: Recycling Contexts for Efficient and Attributed In-Context Learning
IJCNLP 2025
TACT: Advancing Complex Aggregative Reasoning with Information Extraction Tools
NIPS 2024
A Chain-of-Thought Is as Strong as Its Weakest Link: A Benchmark for Verifiers of Reasoning Chains
ACL 2024
Data Contamination Report from the 2024 CONDA Shared Task
ACL 2024
Is It Really Long Context if All You Need Is Retrieval? Towards Genuinely Difficult Long Context NLP
EMNLP 2024
Neighboring Words Affect Human Interpretation of Saliency Explanations
ACL 2023
Stop Uploading Test Data in Plain Text: Practical Strategies for Mitigating Data Contamination by Evaluation Benchmarks
EMNLP 2023
A Comprehensive Evaluation of Tool-Assisted Generation Strategies
EMNLP 2023
Scalable Evaluation and Improvement of Document Set Expansion via Neural Positive-Unlabeled Learning
EACL 2021
Contrastive Explanations for Model Interpretability
EMNLP 2021
Towards Faithfully Interpretable NLP Systems: How Should We Define and Evaluate Faithfulness?
ACL 2020
Exposing Shallow Heuristics of Relation Extraction Models with Challenge Data
EMNLP 2020
Learning and Understanding Different Categories of Sexism Using Convolutional Neural Networkโs Filters
ACL 2019
Neural network gradient-based learning of black-box function interfaces
ICLR 2019
Understanding Convolutional Neural Networks for Text Classification
EMNLP 2018