ML algorithms, training, and inference
Was at Nvidia's GTC conference recently and honestly, it was one of the most eye-opening events I've attended in a while. There was a lot...
I could really use some outside perspective. I’m a senior ML/CV engineer in Canada with about 5–6 years across research and industry. Mas...
Hello, I started researching about AI training Q:Why? R: Because AI training is bad right now. Q: What do you mean its bad? R: Like when ...
![[2603.24961] Can MLLMs Read Students' Minds? Unpacking Multimodal Error Analysis in Handwritten Math](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Abstract page for arXiv paper 2603.24961: Can MLLMs Read Students' Minds? Unpacking Multimodal Error Analysis in Handwritten Math
Abstract page for arXiv paper 2603.24943: FinMCP-Bench: Benchmarking LLM Agents for Real-World Financial Tool Use under the Model Context...
Abstract page for arXiv paper 2603.24933: Decoding Market Emotions in Cryptocurrency Tweets via Predictive Statement Classification with ...
Abstract page for arXiv paper 2603.24929: LogitScope: A Framework for Analyzing LLM Uncertainty Through Information Metrics
Abstract page for arXiv paper 2603.24904: On the Foundations of Trustworthy Artificial Intelligence
Abstract page for arXiv paper 2603.24866: How Far Are Vision-Language Models from Constructing the Real World? A Benchmark for Physical G...
Abstract page for arXiv paper 2603.24853: Resisting Humanization: Ethical Front-End Design Choices in AI for Sensitive Contexts
Abstract page for arXiv paper 2603.24787: ReLope: KL-Regularized LoRA Probes for Multimodal LLM Routing
Abstract page for arXiv paper 2603.24768: Supervising Ralph Wiggum: Exploring a Metacognitive Co-Regulation Agentic AI Loop for Engineeri...
Abstract page for arXiv paper 2603.24747: Formal Semantics for Agentic Tool Protocols: A Process Calculus Approach
Abstract page for arXiv paper 2603.24742: Trust as Monitoring: Evolutionary Dynamics of User Trust and AI Developer Behaviour
Abstract page for arXiv paper 2603.24676: When Is Collective Intelligence a Lottery? Multi-Agent Scaling Laws for Memetic Drift in LLMs
Abstract page for arXiv paper 2603.24621: ARC-AGI-3: A New Challenge for Frontier Agentic Intelligence
I built CodexLib (https://codexlib.io) — a curated repository of 100+ deep knowledge bases in compressed, AI-optimized format. The idea: ...
Most people just type into ChatGPT like it's Google. Claude with a structured system prompt using XML tags behaves like a completely diff...
Hi everyone, I'm a master's student working on anatomy-aware unsupervised anomaly detection in chest X-rays. My thesis uses ADAM v2 (Auto...
Expert Data Science Consultant | 20-Year Track Record As a seasoned data scientist and fractional leader, I excel at tackling complex pro...
Wrote up the process of pushing Qwen 3.5 27B (dense, FP8) to 1.1M total tok/s on 96 B200 GPUs with vLLM v0.18.0. DP=8 nearly 4x'd through...
Energy-based model This article will compare EBMs to multi-layered perceptrons, and addresses a lingering question : Whether or not EBMs ...
Quick insight from building retrieval infrastructure for AI agents: Most agents stuff 50,000 tokens of context into every prompt. They re...
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