#routing

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

2 curated events

papersSEP 10 04:00 UTC

Researchers propose a method to preserve long-tailed expert knowledge in MoE fine-tuning

A new arXiv paper tackles a weakness in adapting Mixture-of-Experts models: routing layers can destabilise during supervised fine-tuning, causing rarely used experts to lose their specialised knowledge. The authors introduce a tuning approach designed to retain this long-tailed expert information and compare it with earlier anti-collapse techniques such as DenseMixer and ESFT. The work addresses a practical bottleneck for teams adapting large MoE models to downstream tasks.

moe/fine-tuning/llms/routing

papersSEP 12 04:00 UTC

RouteRepair: Instance-Level Failure Diagnosis and Targeted Repair for LLM-Designed Routing Heuristics

A new arXiv paper introduces RouteRepair, a framework that diagnoses why LLM-generated heuristics fail on individual routing instances and then applies targeted fixes. The work targets routing optimization in freight, urban logistics, and shared mobility, where good heuristics are needed under tight compute budgets. It is positioned within the growing area of LLM-based automated heuristic design.

llm-agents/optimization/routing/heuristics