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Anil Ramakrishna
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2020 – today
- 2024
- [c22]Elan Markowitz, Anil Ramakrishna, Jwala Dhamala, Ninareh Mehrabi, Charith Peris, Rahul Gupta, Kai-Wei Chang, Aram Galstyan:
Tree-of-Traversals: A Zero-Shot Reasoning Algorithm for Augmenting Black-box Language Models with Knowledge Graphs. ACL (1) 2024: 12302-12319 - [c21]Kshitij Mishra, Tamer Soliman, Anil Ramakrishna, Aram Galstyan, Anoop Kumar:
Correcting Language Model Outputs by Editing Salient Layers. EACL (Findings) 2024: 1295-1305 - [c20]Haw-Shiuan Chang, Nanyun Peng, Mohit Bansal, Anil Ramakrishna, Tagyoung Chung:
Explaining and Improving Contrastive Decoding by Extrapolating the Probabilities of a Huge and Hypothetical LM. EMNLP 2024: 8503-8526 - [c19]Tao Meng, Ninareh Mehrabi, Palash Goyal, Anil Ramakrishna, Aram Galstyan, Richard S. Zemel, Kai-Wei Chang, Rahul Gupta, Charith Peris:
Attribute Controlled Fine-tuning for Large Language Models: A Case Study on Detoxification. EMNLP (Findings) 2024: 13329-13341 - [i13]Tiantian Feng, Anil Ramakrishna, Jimit Majmudar, Charith Peris, Jixuan Wang, Clement Chung, Richard S. Zemel, Morteza Ziyadi, Rahul Gupta:
Partial Federated Learning. CoRR abs/2403.01615 (2024) - [i12]Haw-Shiuan Chang, Nanyun Peng, Mohit Bansal, Anil Ramakrishna, Tagyoung Chung:
REAL Sampling: Boosting Factuality and Diversity of Open-Ended Generation via Asymptotic Entropy. CoRR abs/2406.07735 (2024) - [i11]Duygu Nur Yaldiz, Yavuz Faruk Bakman, Baturalp Buyukates, Chenyang Tao, Anil Ramakrishna, Dimitrios Dimitriadis, Salman Avestimehr:
Do Not Design, Learn: A Trainable Scoring Function for Uncertainty Estimation in Generative LLMs. CoRR abs/2406.11278 (2024) - [i10]Elan Markowitz, Anil Ramakrishna, Jwala Dhamala, Ninareh Mehrabi, Charith Peris, Rahul Gupta, Kai-Wei Chang, Aram Galstyan:
Tree-of-Traversals: A Zero-Shot Reasoning Algorithm for Augmenting Black-box Language Models with Knowledge Graphs. CoRR abs/2407.21358 (2024) - [i9]Tao Meng, Ninareh Mehrabi, Palash Goyal, Anil Ramakrishna, Aram Galstyan, Richard S. Zemel, Kai-Wei Chang, Rahul Gupta, Charith Peris:
Attribute Controlled Fine-tuning for Large Language Models: A Case Study on Detoxification. CoRR abs/2410.05559 (2024) - 2023
- [c18]Anil Ramakrishna, Rahul Gupta, Jens Lehmann, Morteza Ziyadi:
INVITE: a Testbed of Automatically Generated Invalid Questions to Evaluate Large Language Models for Hallucinations. EMNLP (Findings) 2023: 5422-5429 - [c17]Ansel MacLaughlin, Anna Rumshisky, Rinat Khaziev
, Anil Ramakrishna, Yuval Merhav, Rahul Gupta:
Self-Healing Through Error Detection, Attribution, and Retraining. ICASSP 2023: 1-5 - [c16]Zefei Li, Anil Ramakrishna, Anna Rumshisky, Andy Rosenbaum, Saleh Soltan, Rahul Gupta:
Sampling bias in NLU models: Impact and Mitigation. INTERSPEECH 2023: 755-759 - [c15]Tiantian Feng
FedMultimodal: A Benchmark for Multimodal Federated Learning. KDD 2023: 4035-4045 - [i8]Tiantian Feng, Digbalay Bose, Tuo Zhang, Rajat Hebbar, Anil Ramakrishna, Rahul Gupta, Mi Zhang, Salman Avestimehr, Shrikanth Narayanan:
FedMultimodal: A Benchmark For Multimodal Federated Learning. CoRR abs/2306.09486 (2023) - [i7]Ninareh Mehrabi, Palash Goyal, Anil Ramakrishna, Jwala Dhamala, Shalini Ghosh, Richard S. Zemel, Kai-Wei Chang, Aram Galstyan, Rahul Gupta:
JAB: Joint Adversarial Prompting and Belief Augmentation. CoRR abs/2311.09473 (2023) - 2022
- [j2]Anil Ramakrishna
Joint Multi-Dimensional Model for Global and Time-Series Annotations. IEEE Trans. Affect. Comput. 13(1): 473-484 (2022) - [c14]Stefan Schroedl, Manoj Kumar, Kiana Hajebi, Morteza Ziyadi, Sriram Venkatapathy, Anil Ramakrishna, Rahul Gupta, Pradeep Natarajan:
Improving Large-Scale Conversational Assistants using Model Interpretation based Training Sample Selection. EMNLP (Industry Track) 2022: 371-378 - [c13]Rahul Sharma
Federated Learning with Noisy User Feedback. NAACL-HLT 2022: 2726-2739 - [i6]Rahul Sharma, Anil Ramakrishna, Ansel MacLaughlin, Anna Rumshisky, Jimit Majmudar, Clement Chung, Salman Avestimehr, Rahul Gupta:
Federated Learning with Noisy User Feedback. CoRR abs/2205.03092 (2022) - 2021
- [c12]Justin Payan, Yuval Merhav, He Xie, Satyapriya Krishna, Anil Ramakrishna, Mukund Sridhar, Rahul Gupta:
Towards Realistic Single-Task Continuous Learning Research for NER. EMNLP (Findings) 2021: 3773-3783 - [i5]Justin Payan, Yuval Merhav, He Xie, Satyapriya Krishna, Anil Ramakrishna, Mukund Sridhar, Rahul Gupta:
Towards Realistic Single-Task Continuous Learning Research for NER. CoRR abs/2110.14694 (2021) - 2020
- [c11]Anil Ramakrishna, Shrikanth Narayanan:
Sentence Level Estimation of Psycholinguistic Norms Using Joint Multidimensional Annotations. INTERSPEECH 2020: 601-605 - [i4]Anil Ramakrishna, Rahul Gupta, Shrikanth Narayanan:
Joint Multi-Dimensional Model for Global and Time-Series Annotations. CoRR abs/2005.03117 (2020) - [i3]Anil Ramakrishna, Shrikanth Narayanan:
Sentence level estimation of psycholinguistic norms using joint multidimensional annotations. CoRR abs/2005.10232 (2020) - [i2]Victor R. Martinez, Krishna Somandepalli, Karan Singla, Anil Ramakrishna, Yalda T. Uhls, Shrikanth Narayanan:
Victim or Perpetrator? Analysis of Violent Characters Portrayals from Movie Scripts. CoRR abs/2008.08225 (2020)
2010 – 2019
- 2019
- [c10]Victor R. Martinez, Krishna Somandepalli, Karan Singla, Anil Ramakrishna, Yalda T. Uhls, Shrikanth S. Narayanan:
Violence Rating Prediction from Movie Scripts. AAAI 2019: 671-678 - [c9]Victor R. Martinez, Anil Ramakrishna, Ming-Chang Chiu, Karan Singla, Shrikanth S. Narayanan:
A system for the 2019 Sentiment, Emotion and Cognitive State Task of DARPA's LORELEI project. ACII 2019: 1-6 - [i1]Victor R. Martinez, Anil Ramakrishna, Ming-Chang Chiu, Karan Singla, Shrikanth S. Narayanan:
A system for the 2019 Sentiment, Emotion and Cognitive State Task of DARPAs LORELEI project. CoRR abs/1905.00472 (2019) - 2018
- [j1]Nikolaos Malandrakis
The ELISA Situation Frame extraction for low resource languages pipeline for LoReHLT'2016. Mach. Transl. 32(1-2): 127-142 (2018) - [c8]Anil Ramakrishna, Timothy Greer, David C. Atkins, Shrikanth S. Narayanan:
Computational Modeling of Conversational Humor in Psychotherapy. INTERSPEECH 2018: 2344-2348 - 2017
- [c7]Anil Ramakrishna, Victor R. Martinez, Nikolaos Malandrakis, Karan Singla, Shrikanth S. Narayanan:
Linguistic analysis of differences in portrayal of movie characters. ACL (1) 2017: 1669-1678 - 2016
- [c6]Anil Ramakrishna, Rahul Gupta, Ruth B. Grossman, Shrikanth S. Narayanan:
An Expectation Maximization Approach to Joint Modeling of Multidimensional Ratings Derived from Multiple Annotators. INTERSPEECH 2016: 1555-1559 - 2015
- [c5]Anil Ramakrishna, Nikolaos Malandrakis, Elizabeth Staruk, Shrikanth S. Narayanan:
A quantitative analysis of gender differences in movies using psycholinguistic normatives. EMNLP 2015: 1996-2001 - [c4]Tanaya Guha, Zhaojun Yang, Anil Ramakrishna, Ruth B. Grossman, Darren Hedley
On quantifying facial expression-related atypicality of children with Autism Spectrum Disorder. ICASSP 2015: 803-807 - [c3]Daniel Bone, Matthew P. Black, Anil Ramakrishna, Ruth B. Grossman, Shrikanth S. Narayanan:
Acoustic-prosodic correlates of 'awkward' prosody in story retellings from adolescents with autism. INTERSPEECH 2015: 1616-1620 - [c2]David C. Kale, Marjan Ghazvininejad, Anil Ramakrishna, Jingrui He, Yan Liu:
Hierarchical Active Transfer Learning. SDM 2015: 514-522 - 2013
- [c1]Anil Ramakrishna, Yu-Han Chang, Rajiv T. Maheswaran:
An Interactive Web Based Spatio-Temporal Visualization System. ISVC (2) 2013: 673-680
Coauthor Index
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