2 citations · 5 across the 9 of their papers we have counts for
11 papers
Token Signatures of Code: Comparing Coding Behaviors Across Large Language Models
Junpeng Wang, Yuzhong Chen, Menghai Pan +2
The evaluation of large language models (LLMs) on coding tasks has primarily focused on performance metrics such as pass@k. As LLMs continue to advance, many models now meet baseli…
Enhancing Foundation Models in Transaction Understanding with LLM-based Sentence Embeddings
Xiran Fan, Zhimeng Jiang, Chin-Chia Michael Yeh +4
The ubiquity of payment networks generates vast transactional data encoding rich consumer and merchant behavioral patterns. Recent foundation models for transaction analysis proces…
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…
TransactionGPT
Yingtong Dou, Zhimeng Jiang, Tianyi Zhang +26
We present TransactionGPT (TGPT), a foundation model for consumer transaction data within one of the world's largest payment networks. TGPT is designed to understand and generate t…
Illuminating LLM Coding Agents: Visual Analytics for Deeper Understanding and Enhancement
Junpeng Wang, Yuzhong Chen, Menghai Pan +2
Coding agents powered by large language models (LLMs) have gained traction for automating code generation through iterative problem-solving with minimal human involvement. Despite…
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(LLMs) are becoming essential tools for various natural language processing tasks but often suffer from generating outdated or incorrect information.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…
Discrete-state Continuous-time Diffusion for Graph Generation
Zhe Xu, Ruizhong Qiu, Yuzhong Chen +6
Graph is a prevalent discrete data structure, whose generation has wide applications such as drug discovery and circuit design. Diffusion generative models, as an emerging research…
Sketching Multidimensional Time Series for Fast Discord Mining
Chin-Chia Michael Yeh, Yan Zheng, Menghai Pan +7
Time series discords are a useful primitive for time series anomaly detection, and the matrix profile is capable of capturing discord effectively. There exist many research efforts…
Fine-grained Graph Rationalization
Zhe Xu, Menghai Pan, Yuzhong Chen +4
Rationale discovery is defined as finding a subset of the input data that maximally supports the prediction of downstream tasks. In the context of graph machine learning, graph rat…