Geetanjali Bihani
Computer Science · Purdue University West Lafayette
Publications
22
Citations
47
Est. group size
~1
Recurring co-author estimate
Active years
6
Publishing since 2020
Geetanjali Bihani works in natural language processing (NLP), the branch of computer science focused on getting computers to understand and analyze human language. Their work examines when and why language models fail or behave unreliably, including studies of 'shortcut learning' (where models rely on superficial patterns rather than real understanding), model calibration (how well a model's confidence matches its actual accuracy), fairness in model behavior around attributes like occupation, and privacy-preserving methods for text data such as steganography (hiding information within text representations).
Publication output has been steady over the past five years, averaging about 3 papers per year with a consistent yearly presence since 2020.
Generated by claude-sonnet-5 from public bibliographic data · Jul 20, 2026
- Learning Shortcuts: On the Misleading Promise of NLU in Language Models
2025
- The Reliability Paradox: Exploring How Shortcut Learning Undermines Language Model Calibration
Proceedings of the ... Annual Hawaii International Conference on System Sciences/Proceedings of the Annual Hawaii International Conference on System Sciences · 2025
- A Fuzzy Evaluation of Sentence Encoders on Grooming Risk Classification
arXiv (Cornell University) · 2025
- Evaluating Language Models on Grooming Risk Estimation Using Fuzzy Theory
arXiv (Cornell University) · 2025
- Learning Shortcuts: On the Misleading Promise of NLU in Language Models
arXiv (Cornell University) · 2024
- Hire Me or Not? Examining Language Model's Behavior with Occupation Attributes
arXiv (Cornell University) · 2024
- The Reliability Paradox: Exploring How Shortcut Learning Undermines Language Model Calibration
arXiv (Cornell University) · 2024
- Calibration Error Estimation Using Fuzzy Binning
Lecture notes in networks and systems · 2023
- Calibration Error Estimation Using Fuzzy Binning
arXiv (Cornell University) · 2023
- Interpretable Privacy Preservation of Text Representations Using Vector Steganography
Proceedings of the AAAI Conference on Artificial Intelligence · 2022
- On Information Hiding in Natural Language Systems
Proceedings of the ... International Florida Artificial Intelligence Research Society Conference · 2022
- Interpretable Privacy Preservation of Text Representations Using Vector Steganography
2022
- On Information Hiding in Natural Language Systems
arXiv (Cornell University) · 2022
- Low Anisotropy Sense Retrofitting (LASeR) : Towards Isotropic and Sense Enriched Representations
2021
- Interpretable Privacy Preservation of Text Representations Using Vector Steganography
arXiv (Cornell University) · 2021
- arXiv (Cornell University)×11
- Building and Environment×1
- Lecture notes in networks and systems×1
- Figshare×1
- Proceedings of the AAAI Conference on Artificial Intelligence×1
- Yue Qin
Computer Science · Indiana University
- Allen Riddell
Computer Science · Indiana University
- Damir Ćavar
Computer Science · Indiana University
- Elsayed Issa
Computer Science · Purdue University West Lafayette
- Fanyou Wu
Computer Science · Purdue University West Lafayette
This profile was generated automatically from public scholarly data (OpenAlex). Group size and activity levels are estimates derived from co-authorship patterns.
Last updated Jul 20, 2026.
Claim or correct this profile