FailureSensorIQ: A Multi-Choice QA Dataset for Understanding Sensor Relationships and Failure Modes

arXiv:2506.03278 · cs.CL · Submitted 2025-06-03 · Read on arXiv

cs.CL

Submitted: 2025-06-03

Updated: 2026-10-13

Code: https://github.com/IBM/FailureSensorIQ

Terminology

• Benchmark — 3× in this paper · explained in 2 episodes
• Failure Modes — 2× in this paper · explained in 3 episodes
• Benchmarking — 1× in this paper · explained in 4 episodes
• Feature Engineering — 1× in this paper · explained in 3 episodes
• Feature Selection — 1× in this paper · explained in 4 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Multi-Choice Question-Answering — 1× in this paper

Sources

• Phi-4 Technical Report
• Qwen Technical Report
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• LLM-Select: Feature Selection with Large Language Models
• Scaling Instruction-Finetuned Language Models
• ReAct: Synergizing Reasoning and Acting in Language Models

Related papers

• Exploring Solution Divergence and Its Effect on Large Language Model Problem Solving
• Ishigaki-IDS-Bench: A Benchmark for Generating Information Delivery Specification from BIM Information Requirements
• Subliminal Steering: Stronger Encoding of Hidden Signals
• MedStruct-S: A Benchmark for Key Discovery, Key-Conditioned QA and Semi-Structured Extraction from OCR Clinical Reports
• The End of Transformers? On Challenging Attention and the Rise of Sub-Quadratic Architectures
• Untangling the Mechanisms of Misleading Context in Medical Question Answering