AI
Texting with AI can feel off—messages arrive in odd bursts with no real “thinking” pauses. Stephanie2 changes that. * Decides to send or wait: At every step, it chooses to message now or hold, like a human pausing to think. * Natural timing: It models delay as thinking time + typing time,
AI
New research shows that popular language models don’t persuade everyone the same way. Across 13 LLMs and 16 languages, the authors found consistent shifts in tone, appeals, and strategies depending on the recipient’s labeled gender — patterns that mirror well-known gender stereotypes. * Framework tests 19 categories of persuasive language
AI
Can AI help us disagree better? Democracy thrives when diverse voices are heard, but at scale, participation, political equality, and meaningful discussion often pull against each other. New research asks whether AI mediators powered by large language models can ease this trilemma. Building on a recent tool that helped people
AI
AI agents powered by large language models can call tools, but they also hallucinate: picking the wrong tool, sending malformed parameters, or bypassing tools by simulating results. That breaks reliability, security, and audit trails in production. This study shows a lightweight way to catch those mistakes in real time. Instead
AI
How do we know if game-playing AIs can plan, act, and remember like good teammates? Meet MineNPC-Task—a new open benchmark for memory-aware AI agents inside Minecraft’s open world. Instead of toy prompts, tasks come from real co-play sessions with expert players, then get turned into templates with clear
AI
AI meets messy spreadsheets New research shows that large language models (LLMs) struggle when tables are subtly distorted—through small layout or labeling tweaks—even if the data is otherwise standard. * LLMs rarely notice or fix these distortions on their own. * Giving an explicit "watch out for table errors&
AI
LLMs with Retrieval-Augmented Generation (RAG) work better when they read lots of context — but long prompts are slow and pricey. Compressing the context helps, yet models often lose the thread and answer worse. ArcAligner is a lightweight module that helps models make sense of highly compressed context. It "aligns&
AI
Sometimes, vision-language AIs see what the prompt says, not what is in the picture. New research maps how that happens—and how to dial it down. Rudman and colleagues tested object counting with prompts that intentionally overstate what is in an image (for example, "describe four waterlilies" when
AI
As AI models start learning from their own outputs, they risk entering an echo chamber. A new study names this cycle the Self-Consuming Performative Loop (SCPL) and shows how it can warp model behavior over time. * What’s the loop? Deployed models shape what people ask and which data gets
AI
Personalized AI you can read, edit, and take anywhere Most AI systems hide your preferences in opaque vectors. This work makes them plain English instead. Your "profile" becomes a short text summary the model can use across apps and tasks. * Interpretable: you can see and revise what the
AI
Arabic AI users are hitting a hidden speed bump LLM-powered agents are everywhere—but most tests are English-first. Kubrak et al. present the first benchmark to evaluate tool-calling and agentic skills when users prompt in Arabic. * What they built: a standardized way to measure functional accuracy and robustness in Arabic
AI
AI assistants that remember our past chats can feel personalized, but there is a catch. Using all history can anchor them to old habits; using none makes them forget who you are. SteeM (Steerable Memory Agent) introduces a simple idea: a controllable memory dial. * Fresh-start mode: prioritize new ideas and