Faisal Ladhak
- Artificial Intelligence top 5%
- Computer Vision and Pattern Recognition top 10%
- Safety Research top 10%
- Health Informatics top 5%
- Sociology and Political Science
- Co-authors
- Esin DurmusTatsunori HashimotoKathleen McKeownTianyi ZhangPercy LiangDan JurafskyAylin CaliskanDebora Nozza
- Topics
- Topic Modeling (11 papers)Natural Language Processing Techniques (10 papers)Advanced Text Analysis Techniques (6 papers)
- Journals
- Transactions of the Association for Computational LinguisticsRare & Special e-Zone (The Hong Kong University of Science and Technology)Edinburgh Research Explorer
- Partner nations
- United StatesSlovakiaItaly
In The Last Decade
Faisal Ladhak
13 papers receiving 418 citations
Hit Papers
Peers
Comparison fields: 5 of 79
- Artificial Intelligence 303
- Computer Vision and Pattern Recognition 74
- Safety Research 37
- Health Informatics 29
- Sociology and Political Science 27
Countries citing papers authored by Faisal Ladhak
This map shows the geographic impact of Faisal Ladhak'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 Faisal Ladhak with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Faisal Ladhak more than expected).
Fields of papers citing papers by Faisal Ladhak
This network shows the impact of papers produced by Faisal Ladhak. 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 Faisal Ladhak. The network helps show where Faisal Ladhak may publish in the future.
Co-authorship network of co-authors of Faisal Ladhak
This figure shows the co-authorship network connecting the top 25 collaborators of Faisal Ladhak. A scholar is included among the top collaborators of Faisal Ladhak 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 Faisal Ladhak. Faisal Ladhak is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | Smarter, Better, Faster, Longer: A Modern Bidirectional Encoder for Fast, Memory Efficient, and Long Context Finetuning and Inferencebreakdown → | 14 |
| 2 | 0 | |
| 3 | Benchmarking Large Language Models for News Summarizationbreakdown → | 124 |
| 4 | 18 | |
| 5 | 3 | |
| 6 | Easily Accessible Text-to-Image Generation Amplifies Demographic Stereotypes at Large Scalebreakdown → | 118 |
| 7 | 15 | |
| 8 | 3 | |
| 9 | 8 | |
| 10 | 38 | |
| 11 | 11 | |
| 12 | 3 | |
| 13 | 50 | |
| 14 | 38 |
About Faisal Ladhak
Faisal Ladhak is a scholar working on Artificial Intelligence, Computer Vision and Pattern Recognition and Computational Theory and Mathematics, having authored 14 papers that have together received 443 indexed citations. Recurring topics across this work include Topic Modeling (11 papers), Natural Language Processing Techniques (10 papers) and Advanced Text Analysis Techniques (6 papers). The work is most often cited by research in Health Informatics (29 citations), Artificial Intelligence (303 citations) and General Social Sciences (19 citations). Faisal Ladhak has collaborated with scholars based in United States, Slovakia and Italy. Frequent co-authors include Esin Durmus, Tatsunori Hashimoto, Kathleen McKeown, Tianyi Zhang, Percy Liang, Dan Jurafsky, Aylin Caliskan, Debora Nozza, Federico Bianchi and Pratyusha Kalluri. Their work appears in journals such as Transactions of the Association for Computational Linguistics, Rare & Special e-Zone (The Hong Kong University of Science and Technology) and Edinburgh Research Explorer.
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.