Sagar Srinivas

Affiliations:
  • TCS Research, Pune, India


According to our database1, Sagar Srinivas authored at least 27 papers between 2021 and 2024.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of five.

Timeline

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Links

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Bibliography

2024
Towards Automated Patent Workflows: AI-Orchestrated Multi-Agent Framework for Intellectual Property Management and Analysis.
CoRR, 2024

Sparks of Artificial General Intelligence(AGI) in Semiconductor Material Science: Early Explorations into the Next Frontier of Generative AI-Assisted Electron Micrograph Analysis.
CoRR, 2024

EMCNet : Graph-Nets for Electron Micrographs Classification.
CoRR, 2024

Towards Human-Level Understanding of Complex Process Engineering Schematics: A Pedagogical, Introspective Multi-Agent Framework for Open-Domain Question Answering.
CoRR, 2024

Retrieval-Augmented Instruction Tuning for Automated Process Engineering Calculations : A Tool-Chaining Problem-Solving Framework with Attributable Reflection.
CoRR, 2024

Parameter-Efficient Quantized Mixture-of-Experts Meets Vision-Language Instruction Tuning for Semiconductor Electron Micrograph Analysis.
CoRR, 2024

Cross-Modal Learning for Chemistry Property Prediction: Large Language Models Meet Graph Machine Learning.
CoRR, 2024

Knowledge Graph Modeling-Driven Large Language Model Operating System (LLM OS) for Task Automation in Process Engineering Problem-Solving.
CoRR, 2024

Agentic Retrieval-Augmented Generation for Time Series Analysis.
CoRR, 2024

Reprogramming Foundational Large Language Models(LLMs) for Enterprise Adoption for Spatio-Temporal Forecasting Applications: Unveiling a New Era in Copilot-Guided Cross-Modal Time Series Representation Learning.
CoRR, 2024

Hierarchical Network Fusion for Multi-Modal Electron Micrograph Representation Learning with Foundational Large Language Models.
CoRR, 2024

Advancing Enterprise Spatio-Temporal Forecasting Applications: Data Mining Meets Instruction Tuning of Language Models For Multi-modal Time Series Analysis in Low-Resource Settings.
CoRR, 2024

Preliminary Investigations of a Multi-Faceted Robust and Synergistic Approach in Semiconductor Electron Micrograph Analysis: Integrating Vision Transformers with Large Language and Multimodal Models.
CoRR, 2024

Retrieval-Augmented Generation Meets Data-Driven Tabula Rasa Approach for Temporal Knowledge Graph Forecasting.
CoRR, 2024

Foundational Model for Electron Micrograph Analysis: Instruction-Tuning Small-Scale Language-and-Vision Assistant for Enterprise Adoption.
CoRR, 2024

Joint Hypergraph Rewiring and Memory-Augmented Forecasting Techniques in Digital Twin Technology.
CoRR, 2024

Multi-Knowledge Fusion Network for Time Series Representation Learning.
CoRR, 2024

Multi-Source Knowledge-Based Hybrid Neural Framework for Time Series Representation Learning.
CoRR, 2024

Crossing New Frontiers: Knowledge-Augmented Large Language Model Prompting for Zero-Shot Text-Based De Novo Molecule Design.
CoRR, 2024

Vision HgNN: An Electron-Micrograph is Worth Hypergraph of Hypernodes.
CoRR, 2024

Battery GraphNets : Relational Learning for Lithium-ion Batteries(LiBs) Life Estimation.
CoRR, 2024

PointSAGE: Mesh-independent superresolution approach to fluid flow predictions.
CoRR, 2024

Multi-Modal Instruction-Tuning Small-Scale Language-and-Vision Assistant for Semiconductor Electron Micrograph Analysis.
Proceedings of the AAAI 2024 Spring Symposium Series, 2024

2023
Redefining Super-Resolution: Fine-mesh PDE predictions without classical simulations.
CoRR, 2023

Joint Hypergraph Rewiring and Memory-Augmented Forecasting Techniques in Digital Twin Technolog.
Proceedings of the First Workshop on AI for Digital Twins and Cyber-Physical Applications in conjunction with 32nd International Joint Conference on Artificial Intelligence (AI4DT&CP@IJCAI 2023), 2023

2022
Hypergraph Learning based Recommender System for Anomaly Detection, Control and Optimization.
Proceedings of the IEEE International Conference on Big Data, 2022

2021
Universal Adversarial Attack on Deep Learning Based Prognostics.
Proceedings of the 20th IEEE International Conference on Machine Learning and Applications, 2021


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