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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
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#prompting

13 curated events
papersTODAY 04:00 UTC

arXiv paper tests staged prompts across six frontier AI models

A newly posted arXiv paper describes experiments in which the same three-part prompt sequence was run ten times for each of six frontier AI models from OpenAI, Anthropic, xAI and Google DeepMind. The prompts move from asking about architectural preferences toward a fuller task, suggesting the study compares how different systems respond as questioning gets more demanding. The abstract is truncated, so final findings and conclusions are not yet visible.

research/prompting/evaluation/frontier-models
papersTODAY 04:00 UTC

Study examines how users iterate prompts to explore narrative space in LLM story generation

A new arXiv paper analyzes public chatbot logs to understand how people write stories with large language models. The authors find that users repeatedly revise their prompts, tweaking characters and other story elements to explore different narrative directions. The work frames this behavior as navigation through a space of possible stories.

story-generation/prompting/user-behavior/llm
papersTODAY 04:00 UTC

Self-Demonstrations Improve LLM Schema-Ontology Mapping, arXiv Paper Finds

A new arXiv preprint examines how self-demonstrations, where a model generates its own worked examples before answering, affect the task of mapping relational database schemas onto a shared ontology. The authors frame the problem around semantic heterogeneity, obscure table and column names, missing metadata, and the abstraction gap that complicates enterprise knowledge integration. Results reported in the abstract suggest the self-demonstration approach is unexpectedly effective for this mapping task.

llm/ontology/knowledge-graphs/prompting
papersTODAY 04:00 UTC

Audit Finds Persona Prompts Bias Vision-Language Model Affordance Reports

A revised arXiv paper re-examines an earlier seven-prompt study on how vision-language models describe objects and their possible uses under different persona prompts. The authors argue that low overlap between responses alone does not prove an affordance effect, so they add matched-question controls to test whether the differences hold up. The work is a methodological audit aimed at tightening how such prompt-sensitivity claims are evaluated.

vision-language/evaluation/prompting/research
tipsSEP 12 12:40 UTC

OpenAI advises leaner prompts and fewer guardrails for GPT-6 Astra

OpenAI developer Eric Provencher warns that verbose skill descriptions, broad mandatory-reading requirements, and inflexible approval gates can slow down GPT-6 Astra when used in Codex. He recommends that developers trim instructions to fit the specific task and clearly state what a completed job looks like, since stronger models require less detailed guidance.

prompting/openai/codex/gpt-6-astra
papersSEP 10 04:00 UTC

Study compares scored and generated readouts in language models fine-tuned on customer behavior

A new arXiv study investigates whether two common ways of extracting predictions from language models trained on customer behavior data — directly scoring answer probabilities versus having the model generate free-text responses — yield equivalent results. The researchers hold the model checkpoint and prompt content fixed while varying only the elicitation format, allowing a controlled comparison of outcome probabilities across both approaches. The work addresses how interchangeable these readout styles really are in applied predictive settings.

evaluation/llms/prompting/predictive-analytics
papersSEP 10 04:00 UTC

Self-play in code distills a text harness for black-box optimization, arXiv study finds

Researchers explore whether a language-model agent can acquire a numerical search strategy through executable practice and then transfer it as plain text. Targeting low-budget black-box optimization, where unaided LLMs fall short of strong classical optimizers, the approach uses self-play in code to automatically build the harness. The work suggests learned optimization behavior can be distilled into reusable text prompts instead of manually engineered ones.

agents/self-play/optimization/prompting
papersSEP 10 04:00 UTC

Test-time Prompt Refinement Method Reduces Prompt Sensitivity in Text-to-Image Models

A new preprint addresses how text-to-image generators can produce varying results when the wording of a prompt is only slightly changed. The authors present a closed-loop technique that adjusts the prompt during inference, with the goal of making generated images better match the intended meaning. The revised v2 of the arXiv paper describes the approach and its evaluation.

text-to-image/prompting/research/generative-ai
papersSEP 12 04:00 UTC

Soft Prompting Approach Adapts Vision-Language Models with Few Shots

A new arXiv paper tackles few-shot object detection with vision-language models in domains that differ from their training data, such as aerial, industrial, and medical imagery, where only ten labeled images are available. Rather than optimizing discrete text prompts, the authors propose a soft prompting method for adaptation. The work is a cross-listing on arXiv cs.AI.

vision-language/few-shot/prompting/object-detection
papersSEP 12 04:00 UTC

Multimodal Prompts Proposed to Improve LLM Visualization Authoring

A research paper examines how large language models can be guided to build data visualizations, noting that plain natural language instructions often lack the precision needed for exact chart specifications. The authors propose using multimodal prompts that combine text with other input forms to give models clearer direction. The work is presented as a preprint on arXiv and focuses on improving control and accuracy in automated visualization creation.

llm/multimodal/visualization/prompting
tipsSEP 10 06:00 UTC

t3n Guide Explains Deep Research and Offers a Starter Prompt Template

German tech outlet t3n has published a beginner-oriented overview of Deep Research, the practice of running extensive automated research with AI tools. The episode of its MeisterPrompter series includes a prompt template intended to help newcomers get started. It is aimed at readers looking for a practical entry point rather than product announcements.

prompting/deep-research/tutorial/germany
tipsSEP 9 09:39 UTC

Hacker News discussion on asking Claude to change an "Add to Cart" button to blue

A Hacker News thread is built around a deliberately small request to Claude: switch an online store's "Add to Cart" button to blue. The item treats the task as a test of how well AI coding assistants handle narrow, concrete front-end edits. Commenters focus on whether these agent-style coding tools are practical for routine developer chores.

claude/coding-agents/prompting/hacker-news