> International students get hosed paying ~Rmb30,000/yr (~$4,400/yr).man, shit is *so cheap* in China. Bearish for GDP…Blue Bear: Tsinghua… Rmb1,600/yr ($237/yr) dorm fee.Lee Shau Kee Foundation…
**Meta's Muse Spark 1.2** rapidly rose to frontier-tier with top 5 ranking on Vals Index at **$0.69/test**, being **3x cheaper than Kimi** and **10x+ cheaper than…
TIL Paul Erdős prompted his fellow mathematicians with bribes like we did the early LLMs
Prompt injection poses significant security risks to LLM agents. Efficient and effective red-teaming is therefore critical, both for evaluating these risks and for collecting training data…
Article URL: https://www.crimepaysbutbotanydoesnt.com/reading-list Comments URL: https://news.ycombinator.com/item?id=49192566 Points: 64 # Comments: 11
The end of an era.
It is past time to take AI & security seriously at the individual level as well.If its not the current OpenAI and Anthropic models doing it,…
https://preview.redd.it/o6ik6qboeohh1.png?width=1134&format=png&auto=webp&s=4016f26c50c1d93bd3d0c7e880e9b55a2d75310f I have been running Qwen3.6 27b for a little while (mostly coding tasks) and recently trying out V4 flash 0731 in it's place. It was…
As chart images, tabular data, and visualization code play increasingly important roles across diverse domains, cross-representation understanding across these modalities poses fundamental challenges for AI systems:…
Article URL: https://github.com/asamassekou10/ship-safe Comments URL: https://news.ycombinator.com/item?id=49192277 Points: 3 # Comments: 0
Learning generalizable robot manipulation policies requires large-scale and diverse demonstration data. Egocentric human manipulation videos offer rich scene and task diversity, and prior work has shown…
This technical report presents K-EXAONE 2.0, an open-weight multilingual foundation model developed by LG AI Research as a step in our effort toward global frontier-scale foundation…
arXiv:2608.05127v1 Announce Type: cross Abstract: Achieving local differential privacy in distributed optimization while maintaining low communication cost remains challenging. Existing vector quantization methods, such as vqSGD,…
arXiv:2608.04382v1 Announce Type: cross Abstract: Gradient descent has been of particular interest in modern machine learning beyond sole focus on optimization. Implicit bias emerging from optimization,…
arXiv:2607.17607v2 Announce Type: replace-cross Abstract: We study whether stochastic nonconvex optimization can be reduced to ordinary static regret minimization in online convex optimization in a black-box…
arXiv:2608.04348v1 Announce Type: cross Abstract: Multimodal learning of images and tabular data is often impaired by ineffective representations, resulting in redundancy, dispersion, and generalization problems. To…
arXiv:2602.07453v2 Announce Type: replace-cross Abstract: Decision tree ensembles are widely used in critical domains, making robustness and sensitivity analysis essential to their trustworthiness. We study the…
arXiv:2608.04339v1 Announce Type: cross Abstract: Large language models are increasingly used for information seeking, yet semantically equivalent questions phrased in different ways can receive answers of…
arXiv:2507.03897v3 Announce Type: replace-cross Abstract: We introduce GenAI-Powered Inference (GPI), a statistical framework for both causal and predictive inference using unstructured data, including text and images.…
arXiv:2608.04312v1 Announce Type: cross Abstract: Recent proliferation of data-optimization integration has led to a range of methods that aim to improve the statistical performance of data-driven…
arXiv:2304.04374v4 Announce Type: replace-cross Abstract: Proximal causal inference is a framework for evaluating the causal effects in the presence of unmeasured confounding. For point identification, it…
arXiv:2608.04310v1 Announce Type: cross Abstract: The Rashomon effect describes the phenomenon that many models can achieve nearly equivalent performance on the same learning task, with significant…
arXiv:2608.04827v1 Announce Type: new Abstract: We introduce the Intrinsic Hybrid Latent Diffusion Model (ILDM), a generative framework that integrates probabilistic dimensionality reduction with geometry-aware diffusion on…
arXiv:2608.05112v1 Announce Type: new Abstract: The Subspace Constrained Mean Shift (SCMS) algorithm is a popular nonparametric method for extracting density ridges, which serve as a low-dimensional…