self-training

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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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papersTODAY 04:00 UTC

Reward-Guided Self-Training Improves Pronoun Translation in Context-Aware MT

A new arXiv paper examines how context-aware machine translation systems handle pronouns, which depend on discourse information that ordinary fine-tuning tends not to emphasize. The authors propose ProNMT, a self-training approach that uses reward signals to iteratively refine these sparse, context-sensitive decisions while keeping overall translation quality balanced. The work targets the trade-off between general fluency and accurate pronoun-specific output.

machine-translation/self-training/nlp/pronouns

papersTODAY 04:00 UTC

arXiv Paper Proposes MAST for Label-Efficient Biodiversity Sound Detection

Researchers present MAST, a framework for detecting animal vocalizations in passive acoustic recordings while relying on far fewer labeled examples. It combines masked audio pretraining with self-training to improve robustness and transfer across recording sites. The approach aims to make large-scale biodiversity monitoring more practical where expert annotation is costly.

arxiv/audio/self-supervised/biodiversity