LIVE PULSE
5.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.7 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.5 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 src1.8 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 src1.4 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.4 VoiceCodeBench arXiv paper proposes benchmark for exact structured-token recovery in speech recognition — 1 src1.4 Arabic-Russian Parallel Corpus and LLM Benchmark for Scientific Text — 1 src1.4 Study Analyzes Self-Reported Limitations in NLP Research — 1 src5.0 Anthropic CEO Amodei calls for slower AI development and shared safety rules — 11 src2.7 Agility Robotics unveils Digit 5 humanoid for warehouses and factories — 2 src2.5 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 src1.8 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 src1.4 Anthropic data retention policy prompts firms to limit Claude use for sensitive work — 1 src1.4 VoiceCodeBench arXiv paper proposes benchmark for exact structured-token recovery in speech recognition — 1 src1.4 Arabic-Russian Parallel Corpus and LLM Benchmark for Scientific Text — 1 src1.4 Study Analyzes Self-Reported Limitations in NLP Research — 1 src
HEATPULSEAI MAGAZINES
FLIP · FOLLOW · SAVE
Log inSign up

#explainable-ai

3 curated events
papersTODAY 04:00 UTC

Deep Learning Study Targets Biomarkers of Early-Stage Liver Cancer

A new arXiv paper examines whether deep learning and explainable AI methods can help diagnose hepatocellular carcinoma and pinpoint biomarkers across five stages of disease progression. The work uses a transcriptomic biomarker dataset for liver cancer, aiming for models whose predictions can be traced to interpretable biological features. The authors frame it as an early exploration of combining accuracy with explainability in cancer diagnostics.

healthcare/deep-learning/explainable-ai/biomarkers
papersTODAY 04:00 UTC

SAILS: New Method Reveals Functional Form of Feature Interactions in ML Models

A new arXiv paper introduces SAILS, a surrogate-based approach that uses local effect smooths to characterize how features interact inside machine learning models. Unlike prior explanation techniques that only flag or score interactions, or that handle just a narrow set of interaction shapes, SAILS aims to expose the actual functional form of those interactions. The work is posted as a cross-listing on arXiv's cs.AI and cs.LG categories.

interpretability/explainable-ai/research/arxiv
papersSEP 10 04:00 UTC

LM-X: Explainable Vision-Language-Action Model Predicts Progress, Events, and Uncertainty

Researchers introduce LM-X, a framework for vision-language-action robot policies that exposes an explanatory state alongside its actions. Instead of acting as a stimulus-to-action black box, the model natively predicts task progress, notable events, and uncertainty in its decisions. The work aims to bring interpretability to large-scale generalist robot control.

robotics/explainable-ai/multimodal