Publications

Journals

  • Pavalanathan, U., Vivek Datla, Volkova, S., Charles-Smith, L., Pirrung, M., Harrison, J., Chappell, A., & Corley, C. D. (2017). Studying Military Community Health, Well-Being, and Discourse Through the Social Media Lens. Public Health Intelligence and Internet, 87–105.

  • Datla, V. V., Lin, K.-I., & Louwerse, M. M. (2014). Linguistic features predict the truthfulness of short political statements. International Journal of Computational Linguistics and Applications, 5(1), 79–94.

Conferences & Workshops

  • Kumar, A., Samuel, A., Vivek Datla, Pleiss, G., Dutta, S., & Kirchhof, M. (2025). Uncertainty Estimation in LLM-Generated Content. ICML ’25.

  • Zhang, C., Vivek V. Datla, Shrivastava, A., Samuel, A., Huang, Z., Kumar, A., & Liu, D. (2025). An Automatic Method to Estimate Correctness of RAG. In Proceedings of the 31st International Conference on Computational Linguistics (COLING ’25): Industry Track (pp. 603–611). Abu Dhabi, UAE: Association for Computational Linguistics.

  • Ionescu, B., Müller, H., Péteri, R., D. Cid, Y., Liauchuk, V., Kovalev, V., Klimuk, D., Tarasau, A., Abacha, A. B., Hasan, S. A., & Datla, V. (2019, September). ImageCLEF 2019: Multimedia retrieval in medicine, lifelogging, security and nature. In International Conference of the Cross-Language Evaluation Forum for European Languages (pp. 358–386). Springer, Cham.

  • Pandey, R., Shamsuzzaman, M., Hasan, S. A., Sorower, M. S., Khan, M. A. A. H., Liu, J., Vivek Datla, et al. (2019). BoostER: A Performance Boosting Module for Biomedical Entity Recognition. In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 2554–2560). IEEE.

  • Abacha, A. B., Hasan, S. A., Vivek V. Datla, Liu, J., Demner-Fushman, D., & Müller, H. (2019). VQA-Med: Overview of the medical visual question answering task at ImageCLEF 2019. In CLEF 2019 Working Notes (CEUR Workshop Proceedings, pp. 09–12).

  • Khan, M. A. A. H., Shamsuzzaman, M., Hasan, S. A., Sorower, M. S., Liu, J., Vivek Datla, Milosevic, M., Mankovich, G., van Ommering, R., & Dimitrova, N. (2019). Improving Disease Named Entity Recognition for Clinical Trial Matching. In 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 2541–2548). IEEE.

  • Hasan, S. A., Ling, Y., Liu, J., Sreenivasan, R., Anand, S., Arora, T. R., Vivek Datla, et al. (2018). Attention-based medical caption generation with image modality classification and clinical concept mapping. In International Conference of the Cross-Language Evaluation Forum for European Languages (pp. 224–230). Springer, Cham.

  • Ghaeini, R., Hasan, S. A., Vivek Datla, Liu, J., Lee, K., Qadir, A., Ling, Y., Prakash, A., Fern, X., & Farri, O. (2018). DR-BiLSTM: Dependent Reading Bidirectional LSTM for Natural Language Inference. In Proceedings of NAACL-HLT 2018 (pp. 1460–1469).

  • Adduru, V., Hasan, S. A., Liu, J., Ling, Y., Datla, V., Lee, K., … Farri, O. (2018). Towards dataset creation and establishing baselines for sentence-level neural clinical paraphrase generation and simplification. IJCAI-ECAI ’18.

  • Vivek Datla, Arora, T., Liu, J., Adduru, V., Hasan, S. A., Lee, K., Qadir, A., Ling, Y., Prakash, A., & Farri, O. (2017, Oct). Open-Domain Real-Time Question Answering Based on Asynchronous Multi-Perspective Context-Driven Retrieval and Neural Paraphrasing. TREC ’17.

  • Lee, K., Qadir, A., Hasan, S. A., Vivek Datla, Prakash, A., Liu, J., & Farri, O. (2017). Recognizing Tweet Relevance with Profile-Specific and Profile-Independent Supervised Models. TREC ’17.

  • Ling, Y., Hasan, S. A., Liu, J., Lee, K., Vivek Datla, Qadir, A., Farri, O., Filannino, M., Boag, W., Jin, D., Buchan, K. P., & Uzune, O. (2017). A Hybrid Approach to Precision Medicine-Related Biomedical Article Retrieval and Clinical Trial Matching. TREC ’17.

  • Vivek Datla, Hasan, S. A., Qadir, A., Lee, K., Ling, Y., Liu, J., & Farri, O. (2017). Automated Clinical Diagnosis: The Role of Content in Various Sections of a Clinical Document. BHI/BIBM ’17.

  • Ling, Y., Hasan, S. A., Datla, V., Qadir, A., Lee, K., Liu, J., & Farri, O. (2017). Diagnostic Inferencing via Improving Clinical Concept Extraction with Deep Reinforcement Learning: A Preliminary Study. Machine Learning for Healthcare (MLHC) 2017.

  • Lee, K., Qadir, A., Hasan, S. A., Datla, V., Prakash, A., Liu, J., & Farri, O. (2017, April). Adverse Drug Event Detection in Tweets with Semi-Supervised Convolutional Neural Networks. In Proceedings of WWW ’17 (pp. 705–714).

  • Prakash, A., Zhao, S., Hasan, S. A., Vivek Datla, Lee, K., Qadir, A., Liu, J., & Farri, O. (2017). Condensed Memory Networks for Clinical Diagnostic Inferencing. AAAI ’17.

  • Vivek Datla, Hasan, S. A., Liu, J., Lee, K., Qadir, A., Prakash, A., & Farri, O. (2016). Open-Domain Real-Time Question Answering Based on Semantic and Syntactic Question Similarity. TREC ’16.

  • Hasan, S. A., Zhao, S., Vivek Datla, Liu, J., Lee, K., Qadir, A., Prakash, A., & Farri, O. (2016). Clinical Question Answering Using Key-Value Memory Networks and Knowledge Graph. TREC ’16.

  • Hasan, S. A., Liu, B., Liu, J., Qadir, A., Lee, K., Vivek Datla, Prakash, A., & Farri, O. (2016). Neural Clinical Paraphrase Generation with Attention. ClinicalNLP @ COLING ’16, 42.

  • Prakash, A., Hasan, S. A., Lee, K., Vivek Datla, Qadir, A., Liu, J., & Farri, O. (2016). Neural Paraphrase Generation with Stacked Residual LSTM Networks. In Proceedings of COLING 2016 (pp. 2923–2934). Osaka, Japan.

  • Pavalanathan, U., Vivek Datla, Volkova, S., Charles-Smith, L., Pirrung, M., Harrison, J., Chappell, A., & Corley, C. D. (2016). Discourse, Health and Well-Being of Military Populations Through the Social Media Lens. In Proceedings of AAAI W3PHI ’16.

  • Morrison, D. M., Nye, B., Samei, B., Datla, V. V., Kelly, C., & Rus, V. (2014). Building an intelligent pal from the Tutor.com session database—Phase 1: Data mining. In Proceedings of the 7th International Conference on Educational Data Mining (EDM ’14) (pp. 335–336).

  • Datla, V. V., Louwerse, M. M., & Lin, K.-I. (2014). Part of Speech Induction from Distributional Features: Balancing Vocabulary and Context. In Proceedings of the Twenty-Seventh International FLAIRS Conference (FLAIRS ’14) (pp. 28–32). AAAI Press.

  • Datla, V., Lin, K.-I., & Louwerse, M. M. (2012). Capturing disease-symptom relations using higher-order co-occurrence algorithms. In IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

  • Hutchinson, S., Datla, V., & Louwerse, M. M. (2013). Social networks are encoded in language. In Proceedings of the 34th Annual Conference of the Cognitive Science Society (CogSci ’13). Cognitive Science Society.

  • Tillman, R., Datla, V., Hutchinson, S., & Louwerse, M. M. (2013). From head to toe: Embodiment through statistical linguistic frequencies. In Proceedings of CogSci ’13. Cognitive Science Society.

  • Lin, K.-I., Datla, V., Morrison, L., & Louwerse, M. M. (2011). Using a feedback system to enhance chart note quality in Electronic Health Records. In IEEE International Conference on Bioinformatics and Biomedicine (BIBM ’11) (pp. 649–654).

  • Wu, Q., & Datla, V. (2011). On performance modeling and prediction in support of scientific workflow optimization. In Proceedings of the 7th IEEE World Congress on Services (SERVICES ’11). Washington, DC.

  • Wu, Q., Shiva, S., Roy, S., Ellis, C., V. Datla, & Dasgupta, D. (2010). On Modeling and Simulation of Game Theory-based Defense Mechanisms against DoS and DDoS Attacks. In 43rd Annual Simulation Symposium (ANSS ’10), Spring Simulation MultiConference.

  • Franklin, S., Ramamurthy, U., D’Mello, S., McCauley, L., Negatu, A., Silva, R., & Datla, V. (2007). LIDA: A computational model of global workspace theory and developmental learning. In AAAI Fall Symposium on AI and Consciousness. Arlington, VA: AAAI.

Poster Presentations

  • Vivek Datla, Hasan, S. A., Liu, J., Lee, K., Qadir, A., Prakash, A., & Farri, O. (2016). Open-Domain Real-Time Question Answering Based on Semantic and Syntactic Question Similarity. TREC ’16.

  • Datla, V. V., Lin, K.-I., & Louwerse, M. M. (2014). Linguistic features predict the truthfulness of short political statements. CICLing 2014.

  • Vivek Datla, Lin, K.-I., & Louwerse, M. M. (2013). Language encodes verifiability of statements. University of Memphis Research Day (UoM ’13).

  • Louwerse, M. M., Baskar, L., Datla, V., Lin, K.-I., & Morrison, L. (2011). Linguistic features in medical chart notes: How language features benefit our health. Society for Text and Discourse (ST\&D ’11), Poitiers, France.

  • Datla, V. V., Ellis, C., Roy, S., & Sajjan, S. (2011). Game Theory-based Defense Mechanisms against DoS and DDoS Attacks. University of Memphis (UoM ’11).

Preprints

  • Datla, V., & Vishnu, A. (2015). Predicting the top and bottom ranks of Billboard songs using Machine Learning. arXiv:1512.01283.

  • Datla, V., Lin, D., Louwerse, M., & Vishnu, A. (2016). A data-driven approach for semantic role labeling from induced grammar structures in language. arXiv:1606.06274.