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Vineet Kumar

4 accepted papers

2025

LC-Opt: Benchmarking Reinforcement Learning and Agentic AI for End-to-End Liquid Cooling Optimization in Data Centers

Avisek Naug, Antonio Guillen-Perez, Vineet Kumar, Scott Greenwood, Wesley Brewer, Sahand Ghorbanpour +4
NeurIPS 2025poster

Liquid cooling is critical for thermal management in high-density data centers with the rising AI workloads. However, machine learning-based controllers are essential to unlock greater energy efficiency and reliability, promoting sustainability. We present LC-Opt, a Sustainable Liquid Cooling (LC) b…

Cited by 0Source ↗Scholar ↗
2024

Granite-Function Calling Model: Introducing Function Calling Abilities via Multi-task Learning of Granular Tasks

Ibrahim Abdelaziz, Kinjal Basu, Mayank Agarwal, Sadhana Kumaravel, Matthew Stallone, Rameswar Panda +20
EMNLP 2024industry

An emergent research trend explores the use of Large Language Models (LLMs) as the backbone of agentic systems (e.g., SWE-Bench, Agent-Bench). To fulfill LLMs’ potential as autonomous agents, they must be able to identify, call, and interact with a variety of external tools and application program i…

Cited by 21Source ↗PDF ↗code ↗Scholar ↗
2023

Pointwise Mutual Information Based Metric and Decoding Strategy for Faithful Generation in Document Grounded Dialogs

Yatin Nandwani, Vineet Kumar, Dinesh Raghu, Sachindra Joshi, Luis A. Lastras
EMNLP 2023long main

A major concern in using deep learning based generative models for document-grounded dialogs is the potential generation of responses that are not faithful to the underlying document. Existing automated metrics used for evaluating the faithfulness of response with respect to the grounding document m…

Cited by 0Source ↗code ↗Scholar ↗
2022

Gaining Insights into Unrecognized User Utterances in Task-Oriented Dialog Systems

Ella Rabinovich, Matan Vetzler, David Boaz, Vineet Kumar, Gaurav Pandey, Ateret Anaby Tavor
EMNLP 2022industry

The rapidly growing market demand for automatic dialogue agents capable of goal-oriented behavior has caused many tech-industry leaders to invest considerable efforts into task-oriented dialog systems. The success of these systems is highly dependent on the accuracy of their intent identification –…

Cited by 7Source ↗PDF ↗Scholar ↗