Workshop
Workshop on Beyond Market Intelligence: a running collection of 5 stories we have gathered and hand-picked because they are worth your time. Every post here touches on workshop in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around workshop, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.
Epistemic Intelligence in Machine Learning Neurips Workshop page limit? [D]
Submitting to the 3rd Workshop on Epistemic Intelligence in Machine Learning at Neurips requires careful preparation. While the organizers have yet to confirm a specific page limit, historical precedent suggests two likely scenarios: either mirroring the ICML workshop's 6-page limit or aligning with the main Neurips conference’s 9-page constraint. To ensure your paper meets submission guidelines, we recommend erring on the side of brevity. For further exploration of related topics, consider our recent analysis of EMNLP 26 cost considerations.
We’ve got a workshop on production retrieval-augmented generation with open models, benchmarked end to end, thought it’d be relevant here [D]
Unlock production-ready Retrieval-Augmented Generation (RAG) with our upcoming workshop on August 29th. Led by AI Consultant Ben Auffarth, this hands-on session builds and benchmarks end-to-end RAG pipelines using entirely open models—no API calls required. You'll discover hybrid retrieval techniques, crucial reranking strategies, and robust evaluation using RAGAS. Explore cost and performance benchmarking for open-model deployments, all while incorporating guardrails from the outset. Learn more and register here: [https://www.eventbrite.co.uk/e/the-genai-build-lab-build-production-ready-rag-
Why You Shouldn’t Always Trust LLMs as Judges: Understanding Bias in Automated Evaluation
The increasing adoption of Large Language Models (LLMs) for automated evaluation—from assessing code to ranking research—presents a critical challenge. While their speed and scalability are compelling, relying on LLMs as impartial judges demands careful consideration. As highlighted by Bhaskarjit Sarmah at DHS 2026, inherent biases within these models can skew results, undermining the fairness of automated assessments. Explore the nuances of this issue and discover how to navigate this evolving landscape responsibly.
ECCV workshop, camera ready instructions? [D]
Navigating workshop camera-ready submissions can be surprisingly opaque. Many organizers, like those for ECCV, lack readily available instructions, leaving authors understandably uncertain. While some workshops facilitate PDF uploads via OpenReview, crucial details regarding copyright forms and LaTeX source files remain unclear. To ensure a smooth submission process, proactively seek clarification from the workshop team. For broader context on AI-driven workflows and infrastructure supporting research, explore our recent article, "Exclusive: Mirendil inks $100M+ Google Cloud deal to scale self-improving AI."
Neurips Position Track Rebuttal and Reviews [R]
Navigating the NeurIPS Position Track rebuttal process can feel unclear, especially for first-time conference paper submitters. Receiving a 3/3/5/7 alongside reviews with actionable feedback suggests a promising opportunity for revision. The rebuttal phase allows you to directly address reviewer concerns; the Area Chair (AC) will evaluate these rebuttals alongside the original reviews to determine if your revisions adequately address the feedback. Consider referencing "Link plots/figures in NeurIPS rebuttal [R]" for practical guidance on presenting supplementary data effectively.