ForkPilot: Self-Evolving Policy for Retrospective Search in Long-Horizon Agents
Xinyue Zeng, Shivam Shandilya, Guilherme Potje, Leonardo Nunes, Rakshanda Agarwal, Ranveer Chandra, Emre Kiciman, Dawei Zhou, Tusher Chakraborty
October 2026
Leonardo Nunes
Principal Research SDE
论文与出版物
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Diagnosing Capability Gaps in Fine-Tuning Data
Saeid Asgari Taghanaki, Raksha Agarwal, Bruce Sun, Rohan Jha, Elias Stengel-Eskin, Sara Malvar, Rui Ying, Yifei Xu, Guilherme Potje, Tusher Chakraborty, Leonardo Nunes, Ranveer Chandra, Emre Kiciman
April 2026
arXiv | April 2026
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Direct Reasoning Optimization: Constrained RL with Token-Level Dense Reward and Rubric-Gated Constraints for Open-ended Tasks
Yifei Xu, Tusher Chakraborty, Srinagesh Sharma, Leonardo Nunes, Swati Sharma, Kate Drakos Demopulos, Emre Kiciman, Songwu Lu, Ranveer Chandra
Arxiv | June 2025
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Direct Reasoning Optimization: LLMs Can Reward And Refine Their Own Reasoning for Open-Ended Tasks
Yi-Fei Xu, Tusher Chakraborty, Srinagesh Sharma, Leonardo Nunes, Emre Kiciman, Songwu Lu, Ranveer Chandra
ArXiv | June 2025, 第 abs/2506.13351 卷
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RLTHF: Targeted Human Feedback for LLM Alignment
Yifei Xu, Tusher Chakraborty, Emre Kiciman, Bibek Aryal, Eduardo Rodrigues, Srinagesh Sharma, Roberto Estevao, Maria Angels de Luis Balaguer, Jessica Wolk, Rafael Padilha, Leonardo Nunes, Shobana Balakrishna, Songwu Lu, Ranveer Chandra
ICML'25 | February 2025
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Injecting New Knowledge into Large Language Models via Supervised Fine-Tuning
Nick Mecklenburg, Yiyou Lin, Xiaoxiao Li, Daniel Holstein, Leonardo Nunes, Sara Malvar, Bruno Silva, Ranveer Chandra, Vijay Aski, Pavan Kumar Reddy Yannam, Tolga Aktas
ArXiv | April 2024
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RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture
Maria Angels de Luis Balaguer, Vinamra Benara, Renato L. de F. Cunha, Roberto Estevão, Todd Hendry, Daniel Holstein, Jennifer Marsman, Nick Mecklenburg, Sara Malvar, Leonardo Nunes, Rafael Padilha, Morris Sharp, Bruno Silva, Swati Sharma, Vijay Aski, Ranveer Chandra
January 2024
arXiv | January 2024
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GPT-4 as an Agronomist Assistant? Answering Agriculture Exams Using Large Language Models
Bruno Silva, Leonardo Nunes, Roberto Estevão, Vijay Aski, Ranveer Chandra
October 2023
arXiv | October 2023
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Source Attribution and Emissions Quantification for Methane Leak Detection: A Non-Linear Bayesian Regression Approach
Mirco Milletari, Sara Malvar, Yagna Oruganti, Leonardo Nunes, Yazeed Alaudah, Anirudh Badam
The 8th International Online & Onsite Conference on Machine Learning, Optimization, and Data Science | September 2022
Best Paper Award Special Mention
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Unsupervised Machine Learning framework for sensor placement optimization: analyzing methane leaks
Shirui Wang, Sara Malvar, Leonardo Nunes, Kim Whitehall, Yagna Oruganti, Yazeed Alaudah, Anirudh Badam
NeurIPS 2021 Workshop Tackling Climate Change with Machine Learning | December 2021
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ForkPilot: Self-Evolving Policy for Retrospective Search in Long-Horizon Agents
Xinyue Zeng, Shivam Shandilya, Guilherme Potje, Leonardo Nunes, Rakshanda Agarwal, Ranveer Chandra, Emre Kiciman, Dawei Zhou, Tusher Chakraborty
October 2026
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Diagnosing Capability Gaps in Fine-Tuning Data
Saeid Asgari Taghanaki, Raksha Agarwal, Bruce Sun, Rohan Jha, Elias Stengel-Eskin, Sara Malvar, Rui Ying, Yifei Xu, Guilherme Potje, Tusher Chakraborty, Leonardo Nunes, Ranveer Chandra, Emre Kiciman
April 2026
arXiv | April 2026
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Direct Reasoning Optimization: Constrained RL with Token-Level Dense Reward and Rubric-Gated Constraints for Open-ended Tasks
Yifei Xu, Tusher Chakraborty, Srinagesh Sharma, Leonardo Nunes, Swati Sharma, Kate Drakos Demopulos, Emre Kiciman, Songwu Lu, Ranveer Chandra
Arxiv | June 2025
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Direct Reasoning Optimization: LLMs Can Reward And Refine Their Own Reasoning for Open-Ended Tasks
Yi-Fei Xu, Tusher Chakraborty, Srinagesh Sharma, Leonardo Nunes, Emre Kiciman, Songwu Lu, Ranveer Chandra
ArXiv | June 2025, 第 abs/2506.13351 卷
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RLTHF: Targeted Human Feedback for LLM Alignment
Yifei Xu, Tusher Chakraborty, Emre Kiciman, Bibek Aryal, Eduardo Rodrigues, Srinagesh Sharma, Roberto Estevao, Maria Angels de Luis Balaguer, Jessica Wolk, Rafael Padilha, Leonardo Nunes, Shobana Balakrishna, Songwu Lu, Ranveer Chandra
ICML'25 | February 2025
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Injecting New Knowledge into Large Language Models via Supervised Fine-Tuning
Nick Mecklenburg, Yiyou Lin, Xiaoxiao Li, Daniel Holstein, Leonardo Nunes, Sara Malvar, Bruno Silva, Ranveer Chandra, Vijay Aski, Pavan Kumar Reddy Yannam, Tolga Aktas
ArXiv | April 2024
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RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture
Maria Angels de Luis Balaguer, Vinamra Benara, Renato L. de F. Cunha, Roberto Estevão, Todd Hendry, Daniel Holstein, Jennifer Marsman, Nick Mecklenburg, Sara Malvar, Leonardo Nunes, Rafael Padilha, Morris Sharp, Bruno Silva, Swati Sharma, Vijay Aski, Ranveer Chandra
January 2024
arXiv | January 2024
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GPT-4 as an Agronomist Assistant? Answering Agriculture Exams Using Large Language Models
Bruno Silva, Leonardo Nunes, Roberto Estevão, Vijay Aski, Ranveer Chandra
October 2023
arXiv | October 2023
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Source Attribution and Emissions Quantification for Methane Leak Detection: A Non-Linear Bayesian Regression Approach
Mirco Milletari, Sara Malvar, Yagna Oruganti, Leonardo Nunes, Yazeed Alaudah, Anirudh Badam
The 8th International Online & Onsite Conference on Machine Learning, Optimization, and Data Science | September 2022
Best Paper Award Special Mention
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Unsupervised Machine Learning framework for sensor placement optimization: analyzing methane leaks
Shirui Wang, Sara Malvar, Leonardo Nunes, Kim Whitehall, Yagna Oruganti, Yazeed Alaudah, Anirudh Badam
NeurIPS 2021 Workshop Tackling Climate Change with Machine Learning | December 2021
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Injecting New Knowledge into Large Language Models via Supervised Fine-Tuning
Nick Mecklenburg, Yiyou Lin, Xiaoxiao Li, Daniel Holstein, Leonardo Nunes, Sara Malvar, Bruno Silva, Ranveer Chandra, Vijay Aski, Pavan Kumar Reddy Yannam, Tolga Aktas
ArXiv | April 2024
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RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture
Maria Angels de Luis Balaguer, Vinamra Benara, Renato L. de F. Cunha, Roberto Estevão, Todd Hendry, Daniel Holstein, Jennifer Marsman, Nick Mecklenburg, Sara Malvar, Leonardo Nunes, Rafael Padilha, Morris Sharp, Bruno Silva, Swati Sharma, Vijay Aski, Ranveer Chandra
January 2024
arXiv | January 2024
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Source Attribution and Emissions Quantification for Methane Leak Detection: A Non-Linear Bayesian Regression Approach
Mirco Milletari, Sara Malvar, Yagna Oruganti, Leonardo Nunes, Yazeed Alaudah, Anirudh Badam
The 8th International Online & Onsite Conference on Machine Learning, Optimization, and Data Science | September 2022
Best Paper Award Special Mention
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Unsupervised Machine Learning framework for sensor placement optimization: analyzing methane leaks
Shirui Wang, Sara Malvar, Leonardo Nunes, Kim Whitehall, Yagna Oruganti, Yazeed Alaudah, Anirudh Badam
NeurIPS 2021 Workshop Tackling Climate Change with Machine Learning | December 2021
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Unsupervised Machine Learning framework for sensor placement optimization: analyzing methane leaks
Shirui Wang, Sara Malvar, Leonardo Nunes, Kim Whitehall, Yagna Oruganti, Yazeed Alaudah, Anirudh Badam
NeurIPS 2021 Workshop Tackling Climate Change with Machine Learning | December 2021
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ForkPilot: Self-Evolving Policy for Retrospective Search in Long-Horizon Agents
Xinyue Zeng, Shivam Shandilya, Guilherme Potje, Leonardo Nunes, Rakshanda Agarwal, Ranveer Chandra, Emre Kiciman, Dawei Zhou, Tusher Chakraborty
October 2026
-
-
-
Diagnosing Capability Gaps in Fine-Tuning Data
Saeid Asgari Taghanaki, Raksha Agarwal, Bruce Sun, Rohan Jha, Elias Stengel-Eskin, Sara Malvar, Rui Ying, Yifei Xu, Guilherme Potje, Tusher Chakraborty, Leonardo Nunes, Ranveer Chandra, Emre Kiciman
April 2026
arXiv | April 2026
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RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture
Maria Angels de Luis Balaguer, Vinamra Benara, Renato L. de F. Cunha, Roberto Estevão, Todd Hendry, Daniel Holstein, Jennifer Marsman, Nick Mecklenburg, Sara Malvar, Leonardo Nunes, Rafael Padilha, Morris Sharp, Bruno Silva, Swati Sharma, Vijay Aski, Ranveer Chandra
January 2024
arXiv | January 2024
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GPT-4 as an Agronomist Assistant? Answering Agriculture Exams Using Large Language Models
Bruno Silva, Leonardo Nunes, Roberto Estevão, Vijay Aski, Ranveer Chandra
October 2023
arXiv | October 2023
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-
-
Direct Reasoning Optimization: Constrained RL with Token-Level Dense Reward and Rubric-Gated Constraints for Open-ended Tasks
Yifei Xu, Tusher Chakraborty, Srinagesh Sharma, Leonardo Nunes, Swati Sharma, Kate Drakos Demopulos, Emre Kiciman, Songwu Lu, Ranveer Chandra
Arxiv | June 2025
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RLTHF: Targeted Human Feedback for LLM Alignment
Yifei Xu, Tusher Chakraborty, Emre Kiciman, Bibek Aryal, Eduardo Rodrigues, Srinagesh Sharma, Roberto Estevao, Maria Angels de Luis Balaguer, Jessica Wolk, Rafael Padilha, Leonardo Nunes, Shobana Balakrishna, Songwu Lu, Ranveer Chandra
ICML'25 | February 2025
-
Source Attribution and Emissions Quantification for Methane Leak Detection: A Non-Linear Bayesian Regression Approach
Mirco Milletari, Sara Malvar, Yagna Oruganti, Leonardo Nunes, Yazeed Alaudah, Anirudh Badam
The 8th International Online & Onsite Conference on Machine Learning, Optimization, and Data Science | September 2022
Best Paper Award Special Mention
-
Unsupervised Machine Learning framework for sensor placement optimization: analyzing methane leaks
Shirui Wang, Sara Malvar, Leonardo Nunes, Kim Whitehall, Yagna Oruganti, Yazeed Alaudah, Anirudh Badam
NeurIPS 2021 Workshop Tackling Climate Change with Machine Learning | December 2021
-
-
-
Direct Reasoning Optimization: LLMs Can Reward And Refine Their Own Reasoning for Open-Ended Tasks
Yi-Fei Xu, Tusher Chakraborty, Srinagesh Sharma, Leonardo Nunes, Emre Kiciman, Songwu Lu, Ranveer Chandra
ArXiv | June 2025, 第 abs/2506.13351 卷
-
Injecting New Knowledge into Large Language Models via Supervised Fine-Tuning
Nick Mecklenburg, Yiyou Lin, Xiaoxiao Li, Daniel Holstein, Leonardo Nunes, Sara Malvar, Bruno Silva, Ranveer Chandra, Vijay Aski, Pavan Kumar Reddy Yannam, Tolga Aktas
ArXiv | April 2024
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