Daniel Khashabi
- Artificial Intelligence top 1%
- Computer Vision and Pattern Recognition top 2%
- Information Systems top 5%
- Management Science and Operations Research top 10%
- Health Informatics top 5%
- Co-authors
- Dan RothHannaneh HajishirziSwaroop MishraChitta BaralNoah A. SmithTushar KhotSnigdha ChaturvediShyam Upadhyay
- Topics
- Natural Language Processing Techniques (32 papers)Topic Modeling (30 papers)Multimodal Machine Learning Applications (9 papers)
- Partner nations
- United StatesIsraelAustria
In The Last Decade
Daniel Khashabi
40 papers receiving 1.5k citations
Hit Papers
Peers
Comparison fields: 5 of 91
- Artificial Intelligence 1.3k
- Computer Vision and Pattern Recognition 432
- Information Systems 152
- Management Science and Operations Research 74
- Health Informatics 44
Countries citing papers authored by Daniel Khashabi
This map shows the geographic impact of Daniel Khashabi's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Daniel Khashabi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Daniel Khashabi more than expected).
Fields of papers citing papers by Daniel Khashabi
This network shows the impact of papers produced by Daniel Khashabi. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Daniel Khashabi. The network helps show where Daniel Khashabi may publish in the future.
Co-authorship network of co-authors of Daniel Khashabi
This figure shows the co-authorship network connecting the top 25 collaborators of Daniel Khashabi. A scholar is included among the top collaborators of Daniel Khashabi based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Daniel Khashabi. Daniel Khashabi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 0 | |
| 2 | 5 | |
| 3 | 9 | |
| 4 | 6 | |
| 5 | 2 | |
| 6 | 1 | |
| 7 | 1 | |
| 8 | Self-Instruct: Aligning Language Models with Self-Generated Instructionsbreakdown → | 269 |
| 9 | 21 | |
| 10 | Cross-Task Generalization via Natural Language Crowdsourcing Instructionsbreakdown → | 167 |
| 11 | 73 | |
| 12 | 34 | |
| 13 | 22 | |
| 14 | Natural Instructions: Benchmarking Generalization to New Tasks from Natural Language Instructions | 18 |
| 15 | Natural Perturbation for Robust Question Answering | 2 |
| 16 | 196 | |
| 17 | EDISON: Feature Extraction for NLP, Simplified | 7 |
| 18 | Question answering via integer programming over semi-structured knowledge | 12 |
| 19 | Better call Saul: Flexible Programming for Learning and Inference in NLP | 7 |
| 20 | Online learning with adversarial delays | 20 |
About Daniel Khashabi
Daniel Khashabi is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Information Systems, having authored 46 papers that have together received 1.5k indexed citations. Recurring topics across this work include Natural Language Processing Techniques (32 papers), Topic Modeling (30 papers) and Multimodal Machine Learning Applications (9 papers). The work is most often cited by research in Artificial Intelligence (1.3k citations), Health Informatics (44 citations) and Computer Vision and Pattern Recognition (432 citations). Daniel Khashabi has collaborated with scholars based in United States, Israel and Austria. Frequent co-authors include Dan Roth, Hannaneh Hajishirzi, Swaroop Mishra, Chitta Baral, Noah A. Smith, Tushar Khot, Snigdha Chaturvedi, Shyam Upadhyay, Michael Roth and Alisa Liu. Their work appears in journals such as IEEE Transactions on Image Processing, Language Resources and Evaluation and AI Magazine.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.