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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

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2 curated events

papersTODAY 04:00 UTC

Paper compares looped and stacked transformer encoders on 12-lead ECG

A new arXiv preprint examines how recurrent transformers that reuse a single set of weights differ from conventional stacked transformers in representation and dynamics. Using 12-lead electrocardiogram data as the test domain, the authors analyze the mechanistic differences between the two designs. The work aims to clarify the trade-offs behind the parameter efficiency that has made looped architectures popular.

transformers/ecg/research/parameter-efficiency

papersTODAY 04:00 UTC

Study compares eight tokenization strategies for ECG transformer models

A new arXiv paper examines how different tokenization choices affect ECG transformer models, since the tokenizer decides both the physiological signal content the model sees and the sequence length attention operates over. The authors benchmark eight tokenization strategies across four architectures — Transformer, Informer, Reformer, and FEDformer — on the nine-label CPSC ECG dataset. The work is cross-listed in cs.AI and cs.LG.

ecg/tokenization/transformers/benchmark