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

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.

arXiv ProNMT context-aware machine translation pronoun translation reward-guided self-training self-training

COVERAGE · 2 REPORTS · LINKS GO TO THE ORIGINAL OUTLETS

arXiv cs.CLBalancing Global Quality and Pronoun-Specific Feedback for Context-Aware Machine Translation ↗TODAY 04:00 UTC

arXiv cs.AIBalancing Global Quality and Pronoun-Specific Feedback for Context-Aware Machine Translation ↗TODAY 04:00 UTC