Dr-CiK: A Benchmark testing Deep Research for Context-Aided Forecasting
cs.AI, cs.LG
Submitted: 2026-05-27
Updated: 2026-10-02
Code: https://github.com/ServiceNow/Dr-CiK
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- DRBench: A Realistic Benchmark for Enterprise Deep Research
- Phi-4 Technical Report
- Chronos: Learning the Language of Time Series
- Beyond Na\"ive Prompting: Strategies for Improved Context-aided Forecasting with LLMs
- Remember This Event That Year? Assessing Temporal Information and Reasoning in Large Language Models
- Deep Research Bench: Evaluating AI Web Research Agents
- Scaling Open-Ended Reasoning to Predict the Future
- Towards Time Series Reasoning with LLMs
- This Time is Different: An Observability Perspective on Time Series Foundation Models
- A decoder-only foundation model for time-series forecasting
- DeepResearch Bench: A Comprehensive Benchmark for Deep Research Agents
- SysCaps: Language Interfaces for Simulation Surrogates of Complex Systems
- TimeGPT-1
- Monash Time Series Forecasting Archive
- The Llama 3 Herd of Models
- DeepSearchQA: Bridging the Comprehensiveness Gap for Deep Research Agents
- ForecastBench: A Dynamic Benchmark of AI Forecasting Capabilities
- Toto 2.0: Time Series Forecasting Enters the Scaling Era
- Multi-Modal Forecaster: Jointly Predicting Time Series and Textual Data
- Achieving Time Series Reasoning Requires Rethinking Model Design, Tasks Formulation, and Evaluation
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