3 papers
cs.LG2026
Revisiting the Generic Transformer: Deconstructing a Strong Baseline for Time Series Foundation Models
Yunshi Wen, Wesley M. Gifford, Chandra Reddy +3
The recent surge in Time Series Foundation Models has rapidly advanced the field, yet the heterogeneous training setups across studies make it difficult to attribute improvements t…
cs.AI2025
Toward a Trustworthy Optimization Modeling Agent via Verifiable Synthetic Data Generation
Vinicius Lima, Dzung T. Phan, Jayant Kalagnanam +2
We present a framework for training trustworthy large language model (LLM) agents for optimization modeling via a verifiable synthetic data generation pipeline. Focusing on linear…
cs.CL2025
FailureSensorIQ: A Multi-Choice QA Dataset for Understanding Sensor Relationships and Failure Modes
Christodoulos Constantinides, Dhaval Patel, Shuxin Lin +3
We introduce FailureSensorIQ, a novel Multi-Choice Question-Answering (MCQA) benchmarking system designed to assess the ability of Large Language Models (LLMs) to reason and unders…