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ORCIDYash Kumar Lal
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2020 – today
- 2024
[c15]Yash Kumar Lal, Li Zhang, Faeze Brahman, Bodhisattwa Prasad Majumder, Peter Clark, Niket Tandon:
Tailoring with Targeted Precision: Edit-Based Agents for Open-Domain Procedure Customization. ACL (Findings) 2024: 15597-15611- [c14]Gourab Dey, Adithya V. Ganesan, Yash Kumar Lal, Manal Shah, Shreyashee Sinha, Matthew Matero, Salvatore Giorgi, Vivek Kulkarni, H. Andrew Schwartz:
SOCIALITE-LLAMA: An Instruction-Tuned Model for Social Scientific Tasks. EACL (2) 2024: 454-468 - [c13]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 - [i12]Gourab Dey, Adithya V. Ganesan, Yash Kumar Lal, Manal Shah, Shreyashee Sinha, Matthew Matero, Salvatore Giorgi, Vivek Kulkarni, H. Andrew Schwartz:
SOCIALITE-LLAMA: An Instruction-Tuned Model for Social Scientific Tasks. CoRR abs/2402.01980 (2024) - [i11]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) - [i10]Yash Kumar Lal, Preethi Lahoti, Aradhana Sinha, Yao Qin, Ananth Balashankar:
Automated Adversarial Discovery for Safety Classifiers. CoRR abs/2406.17104 (2024) - [i9]Vahid Sadiri Javadi, Johanne R. Trippas, Yash Kumar Lal, Lucie Flek:
Can Stories Help LLMs Reason? Curating Information Space Through Narrative. CoRR abs/2410.19221 (2024) - [i8]Adithya V. Ganesan, Vasudha Varadarajan, Yash Kumar Lal, Veerle C. Eijsbroek, Katarina Kjell, Oscar N. E. Kjell, Tanuja Dhanasekaran, Elizabeth C. Stade, Johannes C. Eichstaedt, Ryan L. Boyd, H. Andrew Schwartz, Lucie Flek:
Explaining GPT-4's Schema of Depression Using Machine Behavior Analysis. CoRR abs/2411.13800 (2024) - 2023
- [c12]Dhruv Verma, Yash Kumar Lal, Shreyashee Sinha, Benjamin Van Durme, Adam Poliak:
Evaluating Paraphrastic Robustness in Textual Entailment Models. ACL (2) 2023: 880-892 - [c11]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 - [c10]Adithya V. Ganesan
, Yash Kumar Lal, August Håkan Nilsson, H. Andrew Schwartz:
Systematic Evaluation of GPT-3 for Zero-Shot Personality Estimation. WASSA@ACL 2023: 390-400 - [i7]Adithya V. Ganesan, Yash Kumar Lal, August Håkan Nilsson, H. Andrew Schwartz:
Systematic Evaluation of GPT-3 for Zero-Shot Personality Estimation. CoRR abs/2306.01183 (2023) - [i6]Dhruv Verma, Yash Kumar Lal, Shreyashee Sinha, Benjamin Van Durme, Adam Poliak:
Evaluating Paraphrastic Robustness in Textual Entailment Models. CoRR abs/2306.16722 (2023) - [i5]Yash Kumar Lal, Li Zhang, Faeze Brahman, Bodhisattwa Prasad Majumder, Peter Clark, Niket Tandon:
One Size Does Not Fit All: Customizing Open-Domain Procedures. CoRR abs/2311.09510 (2023) - 2022
- [c9]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 - 2021
- [c8]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 - [c7]Qingqing Cao, Yash Kumar Lal, Harsh Trivedi, Aruna Balasubramanian, Niranjan Balasubramanian:
IrEne: Interpretable Energy Prediction for Transformers. ACL/IJCNLP (1) 2021: 2145-2157 - [c6]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 - [i4]Qingqing Cao, Yash Kumar Lal, Harsh Trivedi, Aruna Balasubramanian, Niranjan Balasubramanian:
IrEne: Interpretable Energy Prediction for Transformers. CoRR abs/2106.01199 (2021) - [i3]Yash Kumar Lal, Nathanael Chambers, Raymond J. Mooney, Niranjan Balasubramanian:
TellMeWhy: A Dataset for Answering Why-Questions in Narratives. CoRR abs/2106.06132 (2021) - 2020
- [c5]Siddharth Vashishtha, Adam Poliak, Yash Kumar Lal, Benjamin Van Durme, Aaron Steven White:
Temporal Reasoning in Natural Language Inference. EMNLP (Findings) 2020: 4070-4078
2010 – 2019
- 2019
- [c4]Yash Kumar Lal, Vaibhav Kumar, Mrinal Dhar, Manish Shrivastava, Philipp Koehn:
De-Mixing Sentiment from Code-Mixed Text. ACL (2) 2019: 371-377 - [c3]Kelly Marchisio, Yash Kumar Lal, Philipp Koehn:
Johns Hopkins University Submission for WMT News Translation Task. WMT (2) 2019: 287-293 - 2018
- [c2]Yash Kumar Lal, Dhruv Khattar, Vaibhav Kumar, Abhimanshu Mishra, Vasudeva Varma:
Check It Out : Politics and Neural Networks. CLEF (Working Notes) 2018 - [c1]Vaibhav Kumar, Dhruv Khattar, Siddhartha Gairola, Yash Kumar Lal, Vasudeva Varma:
Identifying Clickbait: A Multi-Strategy Approach Using Neural Networks. SIGIR 2018: 1225-1228 - [i2]Vaibhav Kumar, Mrinal Dhar, Dhruv Khattar, Yash Kumar Lal, Abhimanshu Mishra, Manish Shrivastava, Vasudeva Varma:
SWDE : A Sub-Word And Document Embedding Based Engine for Clickbait Detection. CoRR abs/1808.00957 (2018) - 2017
- [i1]Siddhartha Gairola, Yash Kumar Lal, Vaibhav Kumar, Dhruv Khattar:
A Neural Clickbait Detection Engine. CoRR abs/1710.01507 (2017)
Coauthor Index
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