Good grief, we really don't lack benchmarks
LLMS
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AI Model Fine-Tuned for Role-Play as a Bicycle
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The previous edition had an unhinged AI bicycle companion that was fine-tuned to role-play as a bike. If you asked it "what is a transformer?", it'd answer "I don't know, I'm a bike." Absolute 10/10 idea
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Soohak: A Benchmark for Evaluating Research-level Math in LLMs
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Soohak A Mathematician-Curated Benchmark for Evaluating Research-level Math Capabilities of LLMs
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Sharing Papers and Apps on Hugging Face
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Paper:
https://huggingface.co/papers/2605.10922
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App:
https://huggingface.co/spaces/TencentARC/Pixal3D
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Praise for model’s image abstraction capability
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I'm really impressed with how the model is able to reduce the concept of the original image to something so minimal
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Evaluating AI capabilities in complex multi-user interaction scenarios
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Very impressive. I wonder if this passes the test of successfully interacting with two shouting kids that are each asking it different things and interrupting each other. https://t.co/ruaRJZ2gWI
— fofr (@fofrAI) 12 mai 2026Very impressive. I wonder if this passes the test of successfully interacting with two shouting kids that are each asking it different things and interrupting each other.
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Critique on the current state of LLM adoption effectiveness
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We still don't know how to use LLMs effectively btw Far from it in fact
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DeepSeek-TUI: A Terminal-Based Coding Agent for DeepSeek Models
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Hmbown/DeepSeek-TUI: Coding agent for DeepSeek models that runs in your terminal Project: https://
github.com/Hmbown/DeepSee
k-TUI/tree/main
… Our report: https://
mp.weixin.qq.com/s/A7ATOoYGBWwf
1dpV9GIevw
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Open-Source DeepSeek TUI AI Agent Released for Terminal Workflows
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Hunter Bown (a.k.a. "Whale Bro") open-sourced DeepSeek TUI, a terminal-native AI agent built in Rust specifically for DeepSeek V4. It turns your terminal into an AI workstation where you chat, edit files, run shell commands, manage tasks, and even coordinate sub-agents—all with
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The Impact of Prompt Caching on LLM Agentic Workflows and Costs
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Prompt caching didn't even exist until <2 years ago Google: June 2024
Anthropic: August 2024
OpenAI: October 2024 Now for agentic workflows, 95% of tokens gets cached, without it the costs would be completely insane