#submodular

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 src1.7 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 Study traces LLM hallucinations to competing latent associations — 1 src1.3 Arabic-Russian Parallel Corpus and LLM Benchmark for Scientific Text — 1 src1.3 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 src1.7 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 Study traces LLM hallucinations to competing latent associations — 1 src1.3 Arabic-Russian Parallel Corpus and LLM Benchmark for Scientific Text — 1 src1.3 Study Analyzes Self-Reported Limitations in NLP Research — 1 src

2 curated events

papersTODAY 04:00 UTC

Paper Proposes Framework for Linearizable Submodular Optimization

A new arXiv paper introduces upper-linearizable (and quadratizable) functions, a class generalizing concavity and DR-submodularity across monotone and non-monotone settings. The authors present a meta-algorithm that converts algorithms for linearizable problems into ones for this broader class. It is applied to stationary and non-stationary DR-submodular optimization.

optimization/submodular/research/arxiv

papersSEP 10 04:00 UTC

Sharp Barrier Found for Consistent Submodular Maximization

A new paper proves a hardness limit for consistent submodular maximization, where an algorithm keeps at most k elements while the ground set grows over time. It shows that beating the 2-√2 approximation ratio would force either exponentially many queries or recourse that is linear in the number of arrivals. The result sets a boundary on how much solution quality and stability can be improved at once under a monotone submodular objective.

submodular/optimization/theory/algorithms