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2020 – today
- 2024
[c70]Harsh Trivedi, Tushar Khot, Mareike Hartmann, Ruskin Manku, Vinty Dong, Edward Li, Shashank Gupta, Ashish Sabharwal, Niranjan Balasubramanian:
AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents. ACL (1) 2024: 16022-16076- [c69]Sounak Mondal, Seoyoung Ahn, Zhibo Yang, Niranjan Balasubramanian, Dimitris Samaras, Gregory J. Zelinsky, Minh Hoai:
Look Hear: Gaze Prediction for Speech-Directed Human Attention. ECCV (42) 2024: 236-255 - [c68]Yash Kumar Lal, Vanya Cohen, Nathanael Chambers, Niranjan Balasubramanian, Raymond J. Mooney:
CaT-Bench: Benchmarking Language Model Understanding of Causal and Temporal Dependencies in Plans. EMNLP 2024: 19336-19354 - [c67]Nikita Soni, H. Andrew Schwartz, João Sedoc, Niranjan Balasubramanian:
Large Human Language Models: A Need and the Challenges. NAACL-HLT 2024: 8631-8646 - [c66]Chris Tsoukaladelis, Brian Kondracki, Niranjan Balasubramanian, Nick Nikiforakis:
The Times They Are A-Changin': Characterizing Post-Publication Changes to Online News. SP 2024: 1573-1589 - [c65]Nikita Soni, Niranjan Balasubramanian, H. Andrew Schwartz, Dirk Hovy:
Comparing Pre-trained Human Language Models: Is it Better with Human Context as Groups, Individual Traits, or Both? WASSA 2024: 316-328 - [i47]Nikita Soni, Niranjan Balasubramanian, H. Andrew Schwartz, Dirk Hovy:
Comparing Human-Centered Language Modeling: Is it Better to Model Groups, Individual Traits, or Both? CoRR abs/2401.12492 (2024) - [i46]Yash Kumar Lal, Vanya Cohen, Nathanael Chambers, Niranjan Balasubramanian, Raymond Mooney:
CaT-BENCH: Benchmarking Language Model Understanding of Causal and Temporal Dependencies in Plans. CoRR abs/2406.15823 (2024) - [i45]Ha Young Kim, Niranjan Balasubramanian, Byungkon Kang:
On Initializing Transformers with Pre-trained Embeddings. CoRR abs/2407.12514 (2024) - [i44]Harsh Trivedi, Tushar Khot, Mareike Hartmann, Ruskin Manku, Vinty Dong, Edward Li, Shashank Gupta, Ashish Sabharwal, Niranjan Balasubramanian:
AppWorld: A Controllable World of Apps and People for Benchmarking Interactive Coding Agents. CoRR abs/2407.18901 (2024) - [i43]Sounak Mondal, Seoyoung Ahn, Zhibo Yang, Niranjan Balasubramanian, Dimitris Samaras, Gregory J. Zelinsky, Minh Hoai:
Look Hear: Gaze Prediction for Speech-directed Human Attention. CoRR abs/2407.19605 (2024) - [i42]Xueying Bai, Yifan Sun, Niranjan Balasubramanian:
Does RoBERTa Perform Better than BERT in Continual Learning: An Attention Sink Perspective. CoRR abs/2410.05648 (2024) - 2023
- [j5]Marcos V. Treviso, Ji-Ung Lee
, Tianchu Ji, Betty van Aken, Qingqing Cao, Manuel R. Ciosici, Michael Hassid, Kenneth Heafield, Sara Hooker, Colin Raffel, Pedro Henrique Martins, André F. T. Martins, Jessica Zosa Forde, Peter A. Milder, Edwin Simpson, Noam Slonim, Jesse Dodge, Emma Strubell, Niranjan Balasubramanian, Leon Derczynski, Iryna Gurevych, Roy Schwartz:
Efficient Methods for Natural Language Processing: A Survey. Trans. Assoc. Comput. Linguistics 11: 826-860 (2023) - [j4]Sayontan Ghosh, Mahnaz Koupaee, Isabella Chen, Francis Ferraro, Nathanael Chambers, Niranjan Balasubramanian:
PASTA: A Dataset for Modeling PArticipant STAtes in Narratives. Trans. Assoc. Comput. Linguistics 11: 1283-1300 (2023) - [c64]Mohaddeseh Bastan, Mihai Surdeanu, Niranjan Balasubramanian:
NEUROSTRUCTURAL DECODING: Neural Text Generation with Structural Constraints. ACL (1) 2023: 9496-9510 - [c63]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions. ACL (1) 2023: 10014-10037 - [c62]Sayontan Ghosh, Tanvi Aggarwal, Minh Hoai, Niranjan Balasubramanian:
Text-Derived Knowledge Helps Vision: A Simple Cross-modal Distillation for Video-based Action Anticipation. EACL (Findings) 2023: 1837-1852 - [c61]Mahnaz Koupaee, Greg Durrett, Nathanael Chambers, Niranjan Balasubramanian:
Modeling Complex Event Scenarios via Simple Entity-focused Questions. EACL 2023: 2460-2475 - [c60]Sugam Devare, Mahnaz Koupaee, Gautham Gunapati, Sayontan Ghosh, Sai Vallurupalli, Yash Kumar Lal, Francis Ferraro, Nathanael Chambers, Greg Durrett, Raymond J. Mooney, Katrin Erk, Niranjan Balasubramanian:
SAGEViz: SchemA GEneration and Visualization. EMNLP (Demos) 2023: 328-335 - [i41]Mahnaz Koupaee, Greg Durrett, Nathanael Chambers, Niranjan Balasubramanian:
Modeling Complex Event Scenarios via Simple Entity-focused Questions. CoRR abs/2302.07139 (2023) - [i40]Nikita Soni, H. Andrew Schwartz, João Sedoc, Niranjan Balasubramanian:
Large Human Language Models: A Need and the Challenges. CoRR abs/2312.07751 (2023) - 2022
- [j3]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
♫ MuSiQue: Multihop Questions via Single-hop Question Composition. Trans. Assoc. Comput. Linguistics 10: 539-554 (2022) - [c59]Vinh Tran, Niranjan Balasubramanian, Minh Hoai:
From Within to Between: Knowledge Distillation for Cross Modality Retrieval. ACCV (4) 2022: 605-622 - [c58]Nikita Soni, Matthew Matero, Niranjan Balasubramanian, H. Andrew Schwartz:
Human Language Modeling. ACL (Findings) 2022: 622-636 - [c57]Yash Kumar Lal, Niket Tandon, Tanvi Aggarwal, Horace Liu, Nathanael Chambers, Raymond J. Mooney, Niranjan Balasubramanian:
Using Commonsense Knowledge to Answer Why-Questions. EMNLP 2022: 1204-1219 - [c56]Mohaddeseh Bastan, Mihai Surdeanu, Niranjan Balasubramanian:
BioNLI: Generating a Biomedical NLI Dataset Using Lexico-semantic Constraints for Adversarial Examples. EMNLP (Findings) 2022: 5093-5104 - [c55]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Teaching Broad Reasoning Skills for Multi-Step QA by Generating Hard Contexts. EMNLP 2022: 6541-6566 - [c54]Sai Vallurupalli, Sayontan Ghosh, Katrin Erk, Niranjan Balasubramanian, Francis Ferraro:
POQue: Asking Participant-specific Outcome Questions for a Deeper Understanding of Complex Events. EMNLP 2022: 8674-8697 - [c53]Huy Vu, Salvatore Giorgi, Jeremy D. W. Clifton, Niranjan Balasubramanian, H. Andrew Schwartz:
Modeling Latent Dimensions of Human Beliefs. ICWSM 2022: 1064-1074 - [c52]Sayontan Ghosh, Amanpreet Singh, Alex Merenstein, Wei Su, Scott A. Smolka, Erez Zadok, Niranjan Balasubramanian:
SpecNFS: A Challenge Dataset Towards Extracting Formal Models from Natural Language Specifications. LREC 2022: 2166-2176 - [c51]Mohaddeseh Bastan, Nishant Shankar, Mihai Surdeanu, Niranjan Balasubramanian:
SuMe: A Dataset Towards Summarizing Biomedical Mechanisms. LREC 2022: 6922-6931 - [i39]Mohaddeseh Bastan, Nishant Shankar, Mihai Surdeanu, Niranjan Balasubramanian:
SuMe: A Dataset Towards Summarizing Biomedical Mechanisms. CoRR abs/2205.04652 (2022) - [i38]Nikita Soni, Matthew Matero, Niranjan Balasubramanian, H. Andrew Schwartz:
Human Language Modeling. CoRR abs/2205.05128 (2022) - [i37]Xueying Bai, Jinghuan Shang, Yifan Sun, Niranjan Balasubramanian:
Learning for Expressive Task-Related Sentence Representations. CoRR abs/2205.12186 (2022) - [i36]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Teaching Broad Reasoning Skills via Decomposition-Guided Contexts. CoRR abs/2205.12496 (2022) - [i35]Sayontan Ghosh, Mahnaz Koupaee, Isabella Chen, Francis Ferraro, Nathanael Chambers, Niranjan Balasubramanian:
PASTA: A Dataset for Modeling Participant States in Narratives. CoRR abs/2208.00329 (2022) - [i34]Marcos V. Treviso, Tianchu Ji, Ji-Ung Lee, Betty van Aken, Qingqing Cao, Manuel R. Ciosici, Michael Hassid, Kenneth Heafield, Sara Hooker, Pedro Henrique Martins, André F. T. Martins, Peter A. Milder, Colin Raffel, Edwin Simpson, Noam Slonim, Niranjan Balasubramanian, Leon Derczynski, Roy Schwartz:
Efficient Methods for Natural Language Processing: A Survey. CoRR abs/2209.00099 (2022) - [i33]Sayontan Ghosh, Tanvi Aggarwal, Minh Hoai, Niranjan Balasubramanian:
Distilling Knowledge from Language Models for Video-based Action Anticipation. CoRR abs/2210.05991 (2022) - [i32]Mohaddeseh Bastan, Mihai Surdeanu, Niranjan Balasubramanian:
BioNLI: Generating a Biomedical NLI Dataset Using Lexico-semantic Constraints for Adversarial Examples. CoRR abs/2210.14814 (2022) - [i31]Sai Vallurupalli, Sayontan Ghosh, Katrin Erk, Niranjan Balasubramanian, Francis Ferraro:
POQue: Asking Participant-specific Outcome Questions for a Deeper Understanding of Complex Events. CoRR abs/2212.02629 (2022) - [i30]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Interleaving Retrieval with Chain-of-Thought Reasoning for Knowledge-Intensive Multi-Step Questions. CoRR abs/2212.10509 (2022) - 2021
- [j2]Ishita Doshi, Dhritiman Das, Ashish Bhutani, Rajeev Kumar, Rushi Bhatt, Niranjan Balasubramanian:
LANNS: A Web-Scale Approximate Nearest Neighbor Lookup System. Proc. VLDB Endow. 15(4): 850-858 (2021) - [c50]Yash Kumar Lal, Nathanael Chambers, Raymond J. Mooney, Niranjan Balasubramanian:
TellMeWhy: A Dataset for Answering Why-Questions in Narratives. ACL/IJCNLP (Findings) 2021: 596-610 - [c49]Mahnaz Koupaee, Greg Durrett, Nathanael Chambers, Niranjan Balasubramanian:
Don't Let Discourse Confine Your Model: Sequence Perturbations for Improved Event Language Models. ACL/IJCNLP (2) 2021: 599-604 - [c48]Qingqing Cao, Yash Kumar Lal, Harsh Trivedi, Aruna Balasubramanian, Niranjan Balasubramanian:
IrEne: Interpretable Energy Prediction for Transformers. ACL/IJCNLP (1) 2021: 2145-2157 - [c47]Tianchu Ji, Shraddhan Jain, Michael Ferdman, Peter A. Milder, H. Andrew Schwartz, Niranjan Balasubramanian:
On the Distribution, Sparsity, and Inference-time Quantization of Attention Values in Transformers. ACL/IJCNLP (Findings) 2021: 4147-4157 - [c46]Yash Kumar Lal, Reetu Singh, Harsh Trivedi, Qingqing Cao, Aruna Balasubramanian, Niranjan Balasubramanian:
IrEne-viz: Visualizing Energy Consumption of Transformer Models. EMNLP (Demos) 2021: 251-258 - [c45]Matthew Matero, Nikita Soni, Niranjan Balasubramanian, H. Andrew Schwartz:
MeLT: Message-Level Transformer with Masked Document Representations as Pre-Training for Stance Detection. EMNLP (Findings) 2021: 2959-2966 - [c44]Naoya Inoue, Harsh Trivedi, Steven Sinha, Niranjan Balasubramanian, Kentaro Inui:
Summarize-then-Answer: Generating Concise Explanations for Multi-hop Reading Comprehension. EMNLP (1) 2021: 6064-6080 - [c43]Vinh Tran, Niranjan Balasubramanian, Minh Hoai:
Progressive Knowledge Distillation For Early Action Recognition. ICIP 2021: 2583-2587 - [c42]Heeyoung Kwon, Nathanael Chambers, Niranjan Balasubramanian:
Toward Diverse Precondition Generation. *SEM 2021: 160-172 - [i29]Qingqing Cao, Yash Kumar Lal, Harsh Trivedi, Aruna Balasubramanian, Niranjan Balasubramanian:
IrEne: Interpretable Energy Prediction for Transformers. CoRR abs/2106.01199 (2021) - [i28]Tianchu Ji, Shraddhan Jain, Michael Ferdman, Peter A. Milder, H. Andrew Schwartz, Niranjan Balasubramanian:
On the Distribution, Sparsity, and Inference-time Quantization of Attention Values in Transformers. CoRR abs/2106.01335 (2021) - [i27]Yash Kumar Lal, Nathanael Chambers, Raymond J. Mooney, Niranjan Balasubramanian:
TellMeWhy: A Dataset for Answering Why-Questions in Narratives. CoRR abs/2106.06132 (2021) - [i26]Heeyoung Kwon, Nathanael Chambers, Niranjan Balasubramanian:
Toward Diverse Precondition Generation. CoRR abs/2106.07117 (2021) - [i25]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
MuSiQue: Multi-hop Questions via Single-hop Question Composition. CoRR abs/2108.00573 (2021) - [i24]Naoya Inoue, Harsh Trivedi, Steven Sinha, Niranjan Balasubramanian, Kentaro Inui:
Summarize-then-Answer: Generating Concise Explanations for Multi-hop Reading Comprehension. CoRR abs/2109.06853 (2021) - [i23]Matthew Matero, Nikita Soni, Niranjan Balasubramanian, H. Andrew Schwartz:
MeLT: Message-Level Transformer with Masked Document Representations as Pre-Training for Stance Detection. CoRR abs/2109.08113 (2021) - 2020
- [c41]Yingru Liu, Xuewen Yang, Dongliang Xie, Xin Wang, Li Shen, Haozhi Huang, Niranjan Balasubramanian:
Adaptive Activation Network and Functional Regularization for Efficient and Flexible Deep Multi-Task Learning. AAAI 2020: 4924-4931 - [c40]Qingqing Cao, Harsh Trivedi, Aruna Balasubramanian, Niranjan Balasubramanian:
DeFormer: Decomposing Pre-trained Transformers for Faster Question Answering. ACL 2020: 4487-4497 - [c39]Radhika Gaonkar, Heeyoung Kwon, Mohaddeseh Bastan, Niranjan Balasubramanian, Nathanael Chambers:
Modeling Label Semantics for Predicting Emotional Reactions. ACL 2020: 4687-4692 - [c38]Veronica E. Lynn, Niranjan Balasubramanian, H. Andrew Schwartz:
Hierarchical Modeling for User Personality Prediction: The Role of Message-Level Attention. ACL 2020: 5306-5316 - [c37]Mohaddeseh Bastan, Mahnaz Koupaee, Youngseo Son, Richard Sicoli, Niranjan Balasubramanian:
Author's Sentiment Prediction. COLING 2020: 604-615 - [c36]Noah Weber, Leena Shekhar, Heeyoung Kwon, Niranjan Balasubramanian, Nathanael Chambers:
Generating Narrative Text in a Switching Dynamical System. CoNLL 2020: 520-530 - [c35]Zijun Wei, Jianming Zhang, Zhe Lin, Joon-Young Lee, Niranjan Balasubramanian, Minh Hoai, Dimitris Samaras:
Learning Visual Emotion Representations From Web Data. CVPR 2020: 13103-13112 - [c34]Qingqing Cao, Aruna Balasubramanian, Niranjan Balasubramanian:
Towards Accurate and Reliable Energy Measurement of NLP Models. SustaiNLP@EMNLP 2020: 141-148 - [c33]Heeyoung Kwon, Mahnaz Koupaee, Pratyush Singh, Gargi Sawhney, Anmol Shukla, Keerthi Kumar Kallur, Nathanael Chambers, Niranjan Balasubramanian:
Modeling Preconditions in Text with a Crowd-sourced Dataset. EMNLP (Findings) 2020: 3818-3828 - [c32]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Is Multihop QA in DiRe Condition? Measuring and Reducing Disconnected Reasoning. EMNLP (1) 2020: 8846-8863 - [i22]Noah Weber, Leena Shekhar, Heeyoung Kwon, Niranjan Balasubramanian, Nathanael Chambers:
Generating Narrative Text in a Switching Dynamical System. CoRR abs/2004.03762 (2020) - [i21]Qingqing Cao, Harsh Trivedi, Aruna Balasubramanian, Niranjan Balasubramanian:
DeFormer: Decomposing Pre-trained Transformers for Faster Question Answering. CoRR abs/2005.00697 (2020) - [i20]Harsh Trivedi, Niranjan Balasubramanian, Tushar Khot, Ashish Sabharwal:
Measuring and Reducing Non-Multifact Reasoning in Multi-hop Question Answering. CoRR abs/2005.00789 (2020) - [i19]Radhika Gaonkar, Heeyoung Kwon, Mohaddeseh Bastan, Niranjan Balasubramanian, Nathanael Chambers:
Modeling Label Semantics for Predicting Emotional Reactions. CoRR abs/2006.05489 (2020) - [i18]Heeyoung Kwon, Mahnaz Koupaee, Pratyush Singh, Gargi Sawhney, Anmol Shukla, Keerthi Kumar Kallur, Nathanael Chambers, Niranjan Balasubramanian:
Modeling Preconditions in Text with a Crowd-sourced Dataset. CoRR abs/2010.02429 (2020) - [i17]Qingqing Cao, Aruna Balasubramanian, Niranjan Balasubramanian:
Towards Accurate and Reliable Energy Measurement of NLP Models. CoRR abs/2010.05248 (2020) - [i16]Ishita Doshi, Dhritiman Das, Ashish Bhutani, Rajeev Kumar, Rushi Bhatt, Niranjan Balasubramanian:
LANNS: A Web-Scale Approximate Nearest Neighbor Lookup System. CoRR abs/2010.09426 (2020) - [i15]Mohaddeseh Bastan, Mahnaz Koupaee, Youngseo Son, Richard Sicoli, Niranjan Balasubramanian:
Author's Sentiment Prediction. CoRR abs/2011.06128 (2020) - [i14]Amanpreet Singh, Niranjan Balasubramanian:
Open4Business(O4B): An Open Access Dataset for Summarizing Business Documents. CoRR abs/2011.07636 (2020) - [i13]Qingqing Cao, Oriana Riva, Aruna Balasubramanian, Niranjan Balasubramanian:
Bew: Towards Answering Business-Entity-Related Web Questions. CoRR abs/2012.05818 (2020)
2010 – 2019
- 2019
- [c31]Xuewen Yang, Yingru Liu, Dongliang Xie, Xin Wang, Niranjan Balasubramanian:
Latent Part-of-Speech Sequences for Neural Machine Translation. EMNLP/IJCNLP (1) 2019: 780-790 - [c30]Qingqing Cao, Noah Weber, Niranjan Balasubramanian, Aruna Balasubramanian:
DeQA: On-Device Question Answering. MobiSys 2019: 27-40 - [c29]Jun Seok Kang, Robert L. Logan IV, Zewei Chu, Yang Chen, Dheeru Dua, Kevin Gimpel, Sameer Singh, Niranjan Balasubramanian:
PoMo: Generating Entity-Specific Post-Modifiers in Context. NAACL-HLT (1) 2019: 826-838 - [c28]Harsh Trivedi, Heeyoung Kwon, Tushar Khot, Ashish Sabharwal, Niranjan Balasubramanian:
Repurposing Entailment for Multi-Hop Question Answering Tasks. NAACL-HLT (1) 2019: 2948-2958 - [i12]Jun Seok Kang, Robert L. Logan IV, Zewei Chu, Yang Chen, Dheeru Dua, Kevin Gimpel, Sameer Singh, Niranjan Balasubramanian:
PoMo: Generating Entity-Specific Post-Modifiers in Context. CoRR abs/1904.03111 (2019) - [i11]Harsh Trivedi, Heeyoung Kwon, Tushar Khot, Ashish Sabharwal, Niranjan Balasubramanian:
Repurposing Entailment for Multi-Hop Question Answering Tasks. CoRR abs/1904.09380 (2019) - [i10]Xuewen Yang, Yingru Liu, Dongliang Xie, Xin Wang, Niranjan Balasubramanian:
Latent Part-of-Speech Sequences for Neural Machine Translation. CoRR abs/1908.11782 (2019) - [i9]Yingru Liu, Xuewen Yang, Dongliang Xie, Xin Wang, Li Shen, Haozhi Huang, Niranjan Balasubramanian:
Adaptive Activation Network and Functional Regularization for Efficient and Flexible Deep Multi-Task Learning. CoRR abs/1911.08065 (2019) - 2018
- [c27]Noah Weber, Niranjan Balasubramanian, Nathanael Chambers:
Event Representations With Tensor-Based Compositions. AAAI 2018: 4946-4953 - [c26]Heeyoung Kwon, Harsh Trivedi, Peter Jansen, Mihai Surdeanu, Niranjan Balasubramanian:
Controlling Information Aggregation for Complex Question Answering. ECIR 2018: 750-757 - [c25]Mohammadzaman Zamani, H. Andrew Schwartz, Veronica E. Lynn, Salvatore Giorgi, Niranjan Balasubramanian:
Residualized Factor Adaptation for Community Social Media Prediction Tasks. EMNLP 2018: 3560-3569 - [c24]Noah Weber, Leena Shekhar, Niranjan Balasubramanian, Nate Chambers:
Hierarchical Quantized Representations for Script Generation. EMNLP 2018: 3783-3792 - [i8]Noah Weber, Leena Shekhar, Niranjan Balasubramanian, Kyunghyun Cho:
Controlling Decoding for More Abstractive Summaries with Copy-Based Networks. CoRR abs/1803.07038 (2018) - [i7]Noah Weber, Leena Shekhar, Niranjan Balasubramanian:
The Fine Line between Linguistic Generalization and Failure in Seq2Seq-Attention Models. CoRR abs/1805.01445 (2018) - [i6]Viresh Ranjan, Heeyoung Kwon, Niranjan Balasubramanian, Minh Hoai:
Fake Sentence Detection as a Training Task for Sentence Encoding. CoRR abs/1808.03840 (2018) - [i5]Mohammadzaman Zamani, H. Andrew Schwartz, Veronica E. Lynn, Salvatore Giorgi, Niranjan Balasubramanian:
Residualized Factor Adaptation for Community Social Media Prediction Tasks. CoRR abs/1808.09479 (2018) - [i4]Noah Weber, Leena Shekhar, Niranjan Balasubramanian, Nathanael Chambers:
Hierarchical Quantized Representations for Script Generation. CoRR abs/1808.09542 (2018) - 2017
- [c23]Veronica E. Lynn, Youngseo Son, Vivek Kulkarni, Niranjan Balasubramanian, H. Andrew Schwartz:
Human Centered NLP with User-Factor Adaptation. EMNLP 2017: 1146-1155 - [c22]Qingqing Cao, Niranjan Balasubramanian, Aruna Balasubramanian:
MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU. EMDL@MobiSys 2017: 1-6 - [c21]Shashank Jain, Vivek Tiwari, Aruna Balasubramanian, Niranjan Balasubramanian, Supriyo Chakraborty:
PrIA: A Private Intelligent Assistant. HotMobile 2017: 91-96 - [i3]Qingqing Cao, Niranjan Balasubramanian, Aruna Balasubramanian:
MobiRNN: Efficient Recurrent Neural Network Execution on Mobile GPU. CoRR abs/1706.00878 (2017) - [i2]Noah Weber, Niranjan Balasubramanian, Nathanael Chambers:
Event Representations with Tensor-based Compositions. CoRR abs/1711.07611 (2017) - 2016
- [c20]Veronica E. Lynn, Niranjan Balasubramanian, Tahsin M. Kurç, Joel H. Saltz, Rebecca Jacobson:
POE: A Pathology Extraction Tool for Finding Attribute-Value Pairs in Glioma Pathology Reports. AMIA 2016 - [c19]Peter Jansen, Niranjan Balasubramanian, Mihai Surdeanu, Peter Clark:
What's in an Explanation? Characterizing Knowledge and Inference Requirements for Elementary Science Exams. COLING 2016: 2956-2965 - [c18]Samuel Louvan, Chetan Naik, Sadhana Kumaravel, Heeyoung Kwon, Niranjan Balasubramanian, Peter Clark:
Cross Sentence Inference for Process Knowledge. EMNLP 2016: 1442-1451 - 2015
- [c17]Tushar Khot, Niranjan Balasubramanian, Eric Gribkoff, Ashish Sabharwal, Peter Clark, Oren Etzioni:
Exploring Markov Logic Networks for Question Answering. EMNLP 2015: 685-694 - [i1]Tushar Khot, Niranjan Balasubramanian, Eric Gribkoff, Ashish Sabharwal, Peter Clark, Oren Etzioni:
Markov Logic Networks for Natural Language Question Answering. CoRR abs/1507.03045 (2015) - 2013
- [c16]Peter Clark, Philip Harrison, Niranjan Balasubramanian:
A study of the knowledge base requirements for passing an elementary science test. AKBC@CIKM 2013: 37-42 - [c15]Niranjan Balasubramanian, Stephen Soderland, Mausam, Oren Etzioni:
Generating Coherent Event Schemas at Scale. EMNLP 2013: 1721-1731 - 2012
- [c14]Aruna Balasubramanian, Niranjan Balasubramanian, Samuel J. Huston, Donald Metzler, David Wetherall:
FindAll: a local search engine for mobile phones. CoNEXT 2012: 277-288 - [c13]Peter Clark, Philip Harrison, Niranjan Balasubramanian, Oren Etzioni:
Constructing a Textual KB from a Biology TextBook. AKBC-WEKEX@NAACL-HLT 2012: 74-78 - [c12]Niranjan Balasubramanian, Stephen Soderland, Mausam, Oren Etzioni:
Rel-grams: A Probabilistic Model of Relations in Text. AKBC-WEKEX@NAACL-HLT 2012: 101-105 - 2010
- [j1]Niranjan Balasubramanian, Silviu Cucerzan:
Beyond Ranked Lists in Web Search: Aggregating Web Content into Topic Pages. Int. J. Semantic Comput. 4(4): 509-534 (2010) - [c11]Niranjan Balasubramanian, Silviu Cucerzan:
Topic Pages: An Alternative to the Ten Blue Links. ICSC 2010: 353-360 - [c10]Niranjan Balasubramanian, Giridhar Kumaran, Vitor R. Carvalho:
Exploring reductions for long web queries. SIGIR 2010: 571-578 - [c9]Niranjan Balasubramanian, Giridhar Kumaran, Vitor R. Carvalho:
Predicting query performance on the web. SIGIR 2010: 785-786 - [c8]Niranjan Balasubramanian, James Allan:
Learning to select rankers. SIGIR 2010: 855-856
2000 – 2009
- 2009
- [c7]Niranjan Balasubramanian, Silviu Cucerzan:
Automatic generation of topic pages using query-based aspect models. CIKM 2009: 2049-2052 - [c6]Niranjan Balasubramanian, Aruna Balasubramanian, Arun Venkataramani:
Energy consumption in mobile phones: a measurement study and implications for network applications. Internet Measurement Conference 2009: 280-293 - [c5]Niranjan Balasubramanian, James Allan:
Syntactic Query Models for Restatement Retrieval. SPIRE 2009: 143-155 - 2007
- [c4]Özgür Yilmazel, Niranjan Balasubramanian, Sarah Harwell, Jennifer Bailey, Anne Diekema, Elizabeth D. Liddy:
Text Categorization for Aligning Educational Standards. HICSS 2007: 73 - [c3]Niranjan Balasubramanian, James Allan, W. Bruce Croft:
A comparison of sentence retrieval techniques. SIGIR 2007: 813-814 - 2005
- [c2]Özgür Yilmazel, Svetlana Symonenko, Niranjan Balasubramanian, Elizabeth D. Liddy:
Improved Document Representation for Classification Tasks for the Intelligence Community. AAAI Spring Symposium: AI Technologies for Homeland Security 2005: 76-82 - [c1]Özgür Yilmazel, Svetlana Symonenko, Niranjan Balasubramanian, Elizabeth D. Liddy:
Leveraging One-Class SVM and Semantic Analysis to Detect Anomalous Content. ISI 2005: 381-388
Coauthor Index
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