4 citations · 10 across the 7 of their papers we have counts for
9 papers
TREASURE: The Visa Payment Foundation Model for High-Volume Transaction Understanding
Chin-Chia Michael Yeh, Uday Singh Saini, Xin Dai +12
Payment networks form the backbone of modern commerce, generating high volumes of transaction records from daily activities. Properly modeling this data can enable applications suc…
SARA: Selective and Adaptive Retrieval-augmented Generation with Context Compression
Yiqiao Jin, Kartik Sharma, Vineeth Rakesh +4
Retrieval-augmented Generation (RAG) extends large language models (LLMs) with external knowledge but faces key challenges: restricted effective context length and redundancy in re…
Sysformer: Safeguarding Frozen Large Language Models with Adaptive System Prompts
Kartik Sharma, Yiqiao Jin, Vineeth Rakesh +4
As large language models (LLMs) are deployed in safety-critical settings, it is essential to ensure that their responses comply with safety standards. Prior research has revealed t…
MAIN-RAG: Multi-Agent Filtering Retrieval-Augmented Generation
Chia-Yuan Chang, Zhimeng Jiang, Vineeth Rakesh +8
Large Language Models (LLMs) are becoming essential tools for various natural language processing tasks but often suffer from generating outdated or incorrect information. Retrieva…
Transformer-based Models for Long-Form Document Matching: Challenges and Empirical Analysis
Akshita Jha, Adithya Samavedhi, Vineeth Rakesh +2
Recent advances in the area of long document matching have primarily focused on using transformer-based models for long document encoding and matching. There are two primary challe…
SMARTQUERY: An Active Learning Framework for Graph Neural Networks through Hybrid Uncertainty Reduction
Xiaoting Li, Yuhang Wu, Vineeth Rakesh +3
Graph neural networks have achieved significant success in representation learning. However, the performance gains come at a cost; acquiring comprehensive labeled data for training…
Efficacy of Bayesian Neural Networks in Active Learning
Vineeth Rakesh, Swayambhoo Jain
Obtaining labeled data for machine learning tasks can be prohibitively expensive. Active learning mitigates this issue by exploring the unlabeled data space and prioritizing the se…
Matrix Completion in the Unit Hypercube via Structured Matrix Factorization
Emanuele Bugliarello, Swayambhoo Jain, Vineeth Rakesh
Several complex tasks that arise in organizations can be simplified by mapping them into a matrix completion problem. In this paper, we address a key challenge faced by our company…
Linked Causal Variational Autoencoder for Inferring Paired Spillover Effects
Vineeth Rakesh, Ruocheng Guo, Raha Moraffah +2
Modeling spillover effects from observational data is an important problem in economics, business, and other fields of research. % It helps us infer the causality between two seemi…