10 papers
MICA: Multivariate Infini Compressive Attention for Time Series Forecasting
Willa Potosnak, Nina Å»ukowska, MichaÅ WiliÅski +4
Multivariate forecasting with Transformers faces a core scalability challenge: modeling cross-channel dependencies via attention compounds attention's quadratic sequence complexity…
ARFBench: Benchmarking Time Series Question Answering Ability for Software Incident Response
Stephan Xie, Ben Cohen, Mononito Goswami +6
Time series question-answering (TSQA), in which we ask natural language questions to infer and reason about properties of time series, is a promising yet underexplored capability o…
TimeSeriesExamAgent: Creating Time Series Reasoning Benchmarks at Scale
Malgorzata Gwiazda, Yifu Cai, Mononito Goswami +2
Large Language Models (LLMs) have shown promising performance in time series modeling tasks, but do they truly understand time series data? While multiple benchmarks have been prop…
Impermanent: A Live Benchmark for Temporal Generalization in Time Series Forecasting
Azul Garza, Renée Rosillo, Rodrigo Mendoza-Smith +5
Recent advances in time-series forecasting increasingly rely on pre-trained foundation-style models. While these models often claim broad generalization, existing evaluation protoc…
SpIDER: Spatially Informed Dense Embedding Retrieval for Software Issue Localization
Shravan Chaudhari, Rahul Thomas Jacob, Mononito Goswami +3
Retrieving code functions, classes or files that are relevant in order to solve a given user query, bug report or feature request from large codebases is a fundamental challenge fo…
STAMP: Spatial-Temporal Adapter with Multi-Head Pooling
Brad Shook, Abby Turner, Jieshi Chen +4
Time series foundation models (TSFMs) pretrained on data from multiple domains have shown strong performance on diverse modeling tasks. Various efforts have been made to develop fo…