EDINET-Bench: Evaluating LLMs on Complex Financial Tasks using Japanese Financial Statements Paper: https://
pub.sakana.ai/edinet-bench/ We released a Japanese financial benchmark on @Huggingface
, designed to evaluate the performance of LLMs on financial tasks like fraud detection in Japan.
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EDINET-Bench: Evaluating LLMs on Japanese Financial Tasks
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RewardBench 2: New Multi-Skill Reward Model Evaluation Benchmark
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9. RewardBench 2 RewardBench 2 is a new multi-skill benchmark for evaluating reward models with more challenging human prompts and stronger correlation to downstream performance.
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Common Pile v0.1: 8TB Open Licensed Text Dataset for LLM Training
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8. Common Pile v0.1 The Common Pile v0.1 is an 8TB dataset of openly licensed text designed for LLM pretraining, addressing legal and ethical concerns of unlicensed data use.
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5G Technology Powers Elite Sailing Competition Data Analysis
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🌊 Sailing into the Future with 5G Technology 🚀#TFBxSailGP Imagine racing at over 60 mph on a 50-foot foiling catamaran, with 125 sensors capturing 35,000 data points every second, powering a staggering 52 billion data points per day
— Sen. Sally Eaves (@sallyeaves) 8 juin 2025
⛵This is #SailGPNYC – where elite #sport… pic.twitter.com/Egj3lDa3hPSailing into the Future with 5G Technology #TFBxSailGP Imagine racing at over 60 mph on a 50-foot foiling catamaran, with 125 sensors capturing 35,000 data points every second, powering a staggering 52 billion data points per day
This is #SailGPNYC – where elite #sport -
AI Technology Enables Real-Time End-to-End System Transparency
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See how visibility powers smarter decisions.
AI and advanced tech are connecting fragmented systems to deliver real-time, end-to-end transparency in this IDC InfoBrief:
https://
okt.to/6kWDdQ @nvollmer1 @nicochan33 @antgrasso @BlueYonder -
Feature Importance Method Comparison in Machine Learning
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Oh yes, marvelous paper from @FrankRHutter
. Embarrassingly I only discovered it after I was done, although my super-basic approach (regular rf gini feature importance and fairly naive sampling) actually turned out just fine. -
ULMFiT optimization: hyperparameter importance via random forest
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When I was optimising ULMFiT, I came up with a trick where I ran lots of ablations and fed all the hyperparams and results to a random forest. That told me which were most important. I told @l2k about it, and @wandb added it to their product! 😀 https://
youtu.be/2QX6jjMt1Eg?si
=icbhCYqFpt4WEhjP&t=1217
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Real-Time AI Performance Through Edge Computing and Data Streaming
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With 35K data points per second, bonded streams, and AI at the edge, performance emerges as the natural outcome of systems engineered for real-time orchestration under operational pressure. #TFBxSailGP #TFBPartner
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Statistical Bias and Normative Distortion in Model Interpretation
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In statistics, bias is deviation of a model from the structure indicated by the data. In political discussions, bias is generally not a lack of knowledge, but a distortion of a model by normative preferences (suppression of data, possibilities, interpretations one does not like)
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Snorkel Launches Evaluate and Expert Data-as-a-Service
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Specialized AI Starts with Specialized Data We’ve just launched: Snorkel Evaluate Expert Data-as-a-Service More here https://
snorkel.ai/blog/building-
the-ai-data-development-platform-for-specialized-ai/
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