Working with the American Psychological Association on youth mental health and AI
OpenAI and the APA are launching a three-year partnership to develop guidance, resources, and safeguards for responsible AI use supporting youth mental health.
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«How are those Uyghur people doing today? Are there any left?» the brainwashing on Uighur genocide has been insane what happened during Zero Covid? …
«How are those Uyghur people doing today? Are there any left?»the brainwashing on Uighur genocide has been insanewhat happened during Zero Covid? you mean lockdowns?people live…
> International students get hosed paying ~Rmb30,000/yr (~$4,400/yr). man, shit is *so cheap* in China. Bearish for GDP…
> 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…
not much happened today
**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
TIL Paul Erdős prompted his fellow mathematicians with bribes like we did the early LLMs
Agent Against Agent: An Agentic System for Automatic Prompt Injection Red Teaming
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…
Crime Pays but Botany Doesn't
Article URL: https://www.crimepaysbutbotanydoesnt.com/reading-list Comments URL: https://news.ycombinator.com/item?id=49192566 Points: 64 # Comments: 11
[AINews] Jeff, Sanjay, Oriol, and Quoc depart DeepMind; Demis to Chair; Koray to SVP — what is going on at GDM???
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, then the…
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,…
GLM/Qwen Appreciation Post
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…
Consistency-Driven Co-Evolution for Self-Supervised Cross-Representation Learning
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:…
Ship Safe, an open source security scanner for coding agents
Article URL: https://github.com/asamassekou10/ship-safe Comments URL: https://news.ycombinator.com/item?id=49192277 Points: 3 # Comments: 0
Ego2Robot: Scalable Robot Data Synthesis from Egocentric Human Data
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…
K-EXAONE 2.0 Technical Report
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…
SSTQ:Privacy-Preserving Vector Quantization via Subsampled Stochastic TurboQuant
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,…
Non-asymptotic implicit bias of logistic regression at early-stage gradient descent dynamics
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,…
Optimizing the Preconditioner: A Black-box Online-to-Nonconvex Conversion with Static Regret Minimization Oracles
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…
iStructTab: Structured Feature Sequencing for Multimodal Learning of Image and Tabular Data
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…
Data-Aware and Scalable Sensitivity Analysis for Decision Tree Ensembles
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…
Equitable System-Prompt Selection via Constrained Mixed-Strategy GroupDRO
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…
GenAI-Powered Inference
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.…
Achieving First-Order Statistical Improvements in Data-Driven Optimization: From No-Free-Lunch to Amplified Decision Perturbation
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…
Partial Identification of Causal Effects Using Proxy Variables
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…
ArborEnum: Decision Tree Rashomon Sets over Continuous Features
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…