iiinova — where your digital self keeps evolving

Andreas Hochlehnert @ahochlehnert.bsky.social · 26/08/2026

[1/6] 🚨 We’re releasing LAION-BVD: a 10-million-hour open video dataset for multimodal pre-training. - 1.3B video URLs from CommonCrawl - 80M downloaded videos - 10M video hours - 55M captioned clips - 300M frame-caption pairs 🌐: projects.laion.ai/bvd/ 🧵👇

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Andreas Hochlehnert @ahochlehnert.bsky.social · 24/11/2025

🚨 New Paper: "Solving Spatial Supersensing Without Spatial Supersensing" Huge credit to the Cambrian-S team for tackling one of the hardest open problems in video understanding: spatial supersensing. In our paper, we take a closer look at their benchmarks & methods 👇

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Andreas Hochlehnert @ahochlehnert.bsky.social · 08/10/2025

Presenting A Sober Look at Progress in LM Reasoning at @colmweb.org today 🇨🇦 #COLM2025 📅 Today 🕔 11:00 AM – 1:00 PM 📍 Room 710 - Poster #31 We find that many “reasoning” gains fall within variance and show how to make evaluation reproducible again. 📘 bethgelab.github.io/sober-reasoning

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Reposted by Andreas Hochlehnert

Andreas Geiger @andreasgeiger.bsky.social · 20/08/2025

Excited about this new work from @haoyuhe.bsky.social. TLDR: Diffusion language models treat learning and inference differently which lowers performance. RL can be used to overcome this issue for certain problems.

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Andreas Hochlehnert @ahochlehnert.bsky.social · 10/04/2025

🧵1/ 🚨 New paper: A Sober Look at Progress in Language Model Reasoning We re-evaluate recent SFT and RL models for mathematical reasoning and find most gains vanish under rigorous, multi-seed, standardized evaluation. 📊 bethgelab.github.io/sober-reason... 📄 arxiv.org/abs/2504.07086

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Reposted by Andreas Hochlehnert

Prasanna Mayilvahanan @prasannamayil.bsky.social · 18/02/2025

New preprint out! 🎉 How does LLM training loss translate to downstream performance? We show that pretraining data and tokenizer shape loss-to-loss scaling, while architecture and other factors play a surprisingly minor role! brendel-group.github.io/llm-line/ 🧵1/8

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Andreas Hochlehnert @ahochlehnert.bsky.social · 17/02/2025

CuratedThoughts: Data Curation for RL Datasets 🚀 Since DeepSeek-R1 introduced reasoning-based RL, datasets like Open-R1 & OpenThoughts emerged for fine-tuning & GRPO. Our deep dive found major flaws — 25% of OpenThoughts needed elimination by data curation. Here's why 👇🧵

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Reposted by Andreas Hochlehnert

Ofir Press @ofirpress.bsky.social · 17/01/2025

SWE-bench Multimodal evaluation code is out now! SWE-bench MM is a new set of JavaScript issues that have a visual component (‘map isn’t rendering correctly’, ‘button text isn’t appearing’). www.swebench.com/sb-cli/

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Andreas Hochlehnert @ahochlehnert.bsky.social · 13/12/2024

We are presenting CiteMe today at the 11AM poster session (East Exhibit Hall A-C, #3309) CiteMe is a challenging benchmark for LM-based agents to find paper citations, moving beyond simple multiple-choice Q&A to real-world use cases. Come by and say hi :) citeme.ai

citeme.ai

CiteME

CiteME is a benchmark designed to test the abilities of language models in finding papers that are cited in scientific texts.

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Reposted by Andreas Hochlehnert

Sebastian Dziadzio @dziadzio.bsky.social · 19/11/2024

Here's a fledgling starter pack for the AI community in Tübingen. Let me know if you'd like to be added! go.bsky.app/NFbVzrA

go.bsky.app

Tübingen AI

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