27 citations · 87 across the 24 of their papers we have counts for
5 papers · 1 filter
SpIDER: Spatially Informed Dense Embedding Retrieval for Software Issue Localization
Shravan Chaudhari, Rahul Thomas Jacob, Jiajun Cao +3
Retrieving code functions, classes or files relevant to a user query, bug report or feature request from large codebases is a fundamental challenge for Large Language Model (LLM)-b…
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…
Chronos-2: From Univariate to Universal Forecasting
Abdul Fatir Ansari, Oleksandr Shchur, Jaris Küken +20
Pretrained time series models have enabled inference-only forecasting systems that produce accurate predictions without task-specific training. However, existing approaches largely…
TimeSeriesGym: A Scalable Benchmark for (Time Series) Machine Learning Engineering Agents
Yifu Cai, Xinyu Li, Mononito Goswami +3
We introduce TimeSeriesGym, a scalable benchmarking framework for evaluating Artificial Intelligence (AI) agents on time series machine learning engineering challenges. Existing be…
Investigating Compositional Reasoning in Time Series Foundation Models
Willa Potosnak, Cristian Challu, Mononito Goswami +4
Large pre-trained time series foundation models (TSFMs) have demonstrated promising zero-shot performance across a wide range of domains. However, a question remains: Do TSFMs succ…