Machine Learning Blog | ML@CMU | Carnegie Mellon University

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Forking-Sequences — Part II: Multi-Horizon Forecast Ensembling with Reduced Volatility

by Willa Potosnak / August 10, 2026

Based on: Potosnak, W., Wolff, M., Cao, M., Ma, R., Konstantinova, T., Efimov, D., Mahoney, M.W., Oreshkin, B., & Olivares, K.G. "Forking-Sequences: Statistically and Computationally Efficient Multi-Horizon Forecasting with Reduced Volatility." Transactions on Machine Learning Research, 2026. (Disclaimer: Code implementation not used in the paper; not affiliated with Amazon — provided as a reference for forking-sequences and forecast ensembling) TL;DR Ensembling, nearly for free. Forking-sequences already produces overlapping forecasts for every target date across FCDs in a single forward pass,…

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artificial intelligence deep learning machine learning Research

Forking-Sequences — Part I: Statistically and Computationally Efficient Multi-Horizon Forecasting

August 10, 2026

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artificial intelligence computer science machine learning

Healthcare Benchmarks Are Only as Good as Their Assumptions

June 19, 2026

In healthcare settings where patients use LLMs as a medical assistant, LLM performance differs between evaluation and deployment. (a) Bean et al. (2025) find a 61 percentage point difference between evaluation and deployment. (b) We argue this gap arises not…

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artificial intelligence deep learning machine learning Research

Pre-Training Isn’t Bitter Enough

June 17, 2026

Richard Sutton’s “Bitter Lesson” is usually read as a warning against building too much human knowledge into AI systems. Over the long run, the methods that win are not the ones that encode our clever intuition most directly, but the…

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machine learning

Teaching Vision-Language Models to Speak Cinema

May 13, 2026

A year of building a video caption pipeline with 100+ professional creators, and what it taught us about scaling supervision instead of models. By Zhiqiu Lin and Chancharik Mitra. Based on our CVPR 2026 work, Building a Precise Video Language…

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computer vision machine learning reinforcement learning Research

Introducing ARFBench: A time series question-answering benchmark based on real incidents

April 27, 2026

More than a trillion dollars are lost every year due to system failures. To resolve them, engineers must troubleshoot outages quickly. An important task in incident response involves analyzing observability metrics, or time series data that snapshot the health of…

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machine learning

Carnegie Mellon at ICLR 2026

April 20, 2026

CMU researchers are presenting 194 papers at the Fourteenth International Conference on Learning Representations (ICLR 2026), held from April 23rd-April 27th at the Riocentro Convention and Event Center in Rio de Janeiro, Brazil. Here is a quick overview of the…

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machine learning

When Should AI Step Aside?: Teaching Agents When Humans Want to Intervene

April 13, 2026

Recent advances in large language models (LLMs) have enabled AI agents to perform increasingly complex tasks in web navigation. Despite this progress, effective use of such agents continues to rely on human involvement to correct misinterpretations or adjust outputs that…

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artificial intelligence computer science machine learning natural language processing Research

LumberChunker: Long-Form Narrative Document Segmentation

March 17, 2026

Links:Paper | Code | Data LumberChunker lets an LLM decide where a long story should be split, creating more natural chunks that help Retrieval Augmented Generation (RAG) systems retrieve the right information. Introduction Long-form narrative documents usually have an explicit…

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machine learning

Carnegie Mellon at NeurIPS 2025

February 11, 2026

CMU researchers are presenting 156 papers at the Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS 2025), held from December 2nd-December 7th at the San Diego Convention. Here is a quick overview of the areas our researchers are working…

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