Trump calls climate change a con; science braces for more
japantimes.co.jp·19h
🌡️Preservation Thermodynamics
Innovation, openness, and the future of intelligence: an interview with Brigt Harr Vaage
tandfonline.com·12h
🕵Intelligence
How ‘Les Mis’ Became So Successful
nytimes.com·8h
📈Time Series
Author Interview: S.J. Bennett
blog.librarything.com·25m
🏛Digital humanities
Audacity 4: a glimpse of a new, more modern UI for the free audio editor
cdm.link·1d·
Discuss: Hacker News
💿FLAC Archaeology
This Puzzle Shows Just How Far LLMs Have Progressed in a Little Over a Year
towardsdatascience.com·1d
📐Mathematical Art
Cyberpsychology’s Influence on Modern Computing
cacm.acm.org·4h
🎯Threat Hunting
High-precision measurements reveal the energies of nuclear decays
phys.org·1d
🔲Lattice Cryptography
AI Fixed Coding, but Not the Bottleneck: Why Lisp, FP Still Matters
github.com·18h·
Discuss: Hacker News, r/neovim
🔗Lisp
How I Actually Use Statistics as a Data Scientist
kdnuggets.com·1d
🧪Data science
Beyond Transformers: Can MLPs Unlock the Potential of In-Context Learning?
dev.to·23h·
Discuss: DEV
🌳Context free grammars
Med-K2N: Flexible K-to-N Modality Translation for Medical Image Synthesis
arxiv.org·2d
🧠Machine Learning
From Theory to Practice: Evaluating Data Poisoning Attacks and Defenses in In-Context Learning on Social Media Health Discourse
arxiv.org·1d
🔗Monadic Parsing
Evaluating LLM Safety Across Child Development Stages: A Simulated Agent Approach
arxiv.org·15h
💻Programming languages
From "Arbitrary Timberland" To "Skyline Charts": Is Visualization At Risk From The Pollution of Scientific Literature?
arxiv.org·15h
📊Citation Graphs
Carbon Emission Prediction in China Considering New Quality Productive Forces Using a Deep & Corss Learning Modeling Framework
arxiv.org·15h
🧠Machine Learning
Efficient Test-Time Scaling for Small Vision-Language Models
arxiv.org·1d
🗜️LZW Variants
Read Between the Lines: A Benchmark for Uncovering Political Bias in Bangla News Articles
arxiv.org·1d
⚙️Compression Benchmarking
Quant-dLLM: Post-Training Extreme Low-Bit Quantization for Diffusion Large Language Models
arxiv.org·1d
💻Local LLMs
Context Matters: Learning Global Semantics for Visual Reasoning and Comprehension
arxiv.org·15h
📊Learned Metrics