LIVE PULSE
4.9 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.6 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.4 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src2.2 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.7 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.4 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.3 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.3 CoMem Paper Proposes Shared and Individual Memory Design for LLM Multi-Agent Systems — 1 src1.3 Paper proposes evolving context parameterization for large language models — 1 src1.3 Fine-Tuning Vision-Language Models with Listener Gaze for Referring Expressions — 1 src4.9 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.6 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.4 Apple ships rebuilt Siri with Google Gemini, but not in the EU — 2 src2.2 Siri AI in macOS 27 Golden Gate: FAQ, Germany availability, privacy questions — 2 src1.7 Sam Altman says OpenAI will not go public in 2026, citing AI safety concerns — 5 src1.4 OpenAI contractors review real ChatGPT conversations to rate responses, report says — 2 src1.3 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.3 CoMem Paper Proposes Shared and Individual Memory Design for LLM Multi-Agent Systems — 1 src1.3 Paper proposes evolving context parameterization for large language models — 1 src1.3 Fine-Tuning Vision-Language Models with Listener Gaze for Referring Expressions — 1 src
HEATPULSEAI MAGAZINES
FLIP · FOLLOW · SAVE
Log inSign up

Adversarial machine learning

topic3 events
papersTODAY 04:00 UTC

Study Reexamines How Effective Targeted Data Poisoning Attacks Really Are

A new arXiv paper argues that common evaluations of targeted data poisoning attacks are misleading because they average success rates across randomly chosen test targets, which masks worst-case outcomes. The author(s) suggest that this averaging can overstate or understate the practical threat depending on the specific samples an adversary cares about. The work calls for evaluation protocols that account for per-target variation rather than relying on aggregate scores.

data-poisoning/adversarial-ml/safety/benchmarks
papersTODAY 04:00 UTC

Whetstones: Coevolution Between Adaptive Malware and Behavioral Defense

A new arXiv paper argues that most research on self-adapting malware is open-loop, testing adaptation only against fixed detectors in simulations with experimenter-defined fitness. The authors instead build both the adaptive malware and the behavioral defense, letting each side influence the other in a closed feedback loop. They frame this setup as a way to measure how offensive and defensive techniques coevolve over time.

malware/security/adversarial/research
papersSEP 10 04:00 UTC

Researchers study sequence prediction when the oracle can lie

A new machine learning theory paper on arXiv examines how a learner can predict elements of a sequence when the oracle supplying feedback may misreport outcomes. The authors frame the task as a repeated interaction in which the environment picks an outcome from a finite alphabet and the learner must commit to a probability distribution without reliable ground truth. The work analyzes what prediction performance can still be guaranteed in this adversarial setting.

learning-theory/prediction/adversarial/research