PISCO is a video AI that lets you place a specific object into a real video exactly where and when you want, using just a few keyframes instead of editing every frame.
AgenticPay is a safe playground where AI agents practice buying and selling by talking, not just by typing numbers.
The paper introduces CoPE, a simple change to how models track word positions that makes long documents much easier for them to understand.
When you tune the learning rate carefully, plain old LoRA fine-tuning works about as well as fancy new versions.
This paper says today's content AIs are great at pretty pictures and videos but often miss what people actually want, creating a big Intent-Execution Gap.
Binary right/wrong rewards for training reasoning in large language models are hard to design and often too sparse to learn from.
AOrchestra is like a smart conductor that builds the right mini-helpers (sub-agents) on demand to solve big, multi-step tasks.
CL-bench is a new test that checks whether AI can truly learn new things from the information you give it right now, not just from what it memorized before.
RLAnything is a new reinforcement learning (RL) framework that trains three things together at once: the policy (the agent), the reward model (the judge), and the environment (the tasks).
The paper tackles a new kind of search called Wide Research, where an AI must gather lots of related facts under complex rules and put them into a clean table.
Kimi K2.5 is a new open-source AI that can read both text and visuals (images and videos) and act like a team of helpers to finish big tasks faster.
WildGraphBench is a new test that checks how well GraphRAG systems find and combine facts from messy, real-world web pages.