Measuring AI Agents as Teammates with Collaborative Intelligence
Progress in AI is often measured by what a single model can do on its own. Yet teams of AI agents are starting
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46 件Progress in AI is often measured by what a single model can do on its own. Yet teams of AI agents are starting
Computer graphics is built on code. Large language model (LLM) agents can now generate graphics code and itera
Coding agents solve repository issues through long sequences of exploration, editing, and validation. These tr
Scaling computer-use agents from individual actions to complex software work requires experience that connects
As coding agents achieve increasingly high success rates on software engineering benchmarks, recent efforts ha
Streaming video LLMs can now commentate live gameplay, but they are trained and tested on the same games. We s
Robot agents built on vision-language models depend on both the planner and its harness: the tools, feedback,
Existing sketch generation methods often rely on image guidance and are largely limited to individual objects
Video generation is shifting from end-to-end synthesis toward agentic generation, where planning, tool use, an
Large language model (LLM)-based multi-agent systems (MAS) coordinate specialized agents to solve complex task
Progress toward artificial general intelligence (AGI) has largely relied on scaling a resource-intensive execu
Recent advances in video world models have enabled the generation of increasingly realistic and interactive vi
Across coding, web, and tool-use tasks, language-model agents are now routinely trained with the same recipe:
To succeed in real-world long-horizon software development, coding agents must satisfy multi-dimensional task
Proactive agents must decide whether, when, and how far to assist without an explicit request. Existing evalua
An effective agent memory system should adapt to a user's history and task requirements. Human-annotated super
A voice agent's speech recognizer transcribes everyone near the microphone, including people other than the ca
Do research agents have taste, the judgment of which experiments are worth running before their outcomes are k
As publications and products on time series forecasting (TSF) proliferate, researchers face a growing burden o
We present Youtu-Parsing-Omni, an omni-modal parser that converts documents, images, audio, and video into str
Agentic image editors decompose complex requests into steps, but when a step fails, they mostly retry with the
While frontier vision-language models demonstrate strong capabilities in user interface (UI) navigation, their
Producing long-form videos from narration requires interdependent decisions that remain coherent across shots.
Financial agents must form forecasts and investment judgments from decision-time evidence, with predictions ev
Recent advances in multimodal large language models have increased interest in interaction paradigms for video
We present EasyProver, a Lean proving system built from recursive agents with isolated contexts, asynchronous
Quarterly earnings forecasting requires an agent to connect financial evidence to the income-statement line it
Existing multi-agent collaboration (MAC) methods have primarily explored a group thinking collaboration topolo
Large Language Models (LLMs) are increasingly used in multi-turn agentic workloads that require sustained inte
Large language model agents are increasingly used for scientific discovery. However, existing benchmarks mix l
Scaling supervised training for working agents requires diverse professional tasks that yield reliable expert
Web agents require diverse, executable, and resettable website environments for reproducible training and eval
Low-cost arms such as the SO-101 have become the most common entry point to robot learning, yet no released po
Agentic services alternate between model inference on clustered GPUs and external tools on distributed CPUs. I
Multi-agent systems (MAS) require both effective coordination and specialized task execution. Existing prompt
Evaluating human-AI co-design requires testing whether coding agents can translate real users' multimodal requ
As frontier language models grow increasingly capable and autonomous, independent third-party evaluations are
Language agents increasingly act through external tools and interactive environments, making the interface bet
In recent years, agentic orchestration has been widely applied to solve complex human tasks. However, existing
Large language model agents have enabled software development through natural-language interaction, but extend
Recent advances in large (vision) language models have enabled computer-use agents that automate digital workf
Realistic market impact is essential for generative limit order book (LOB) models to serve as world models for
Blockchain forensics is adversarial and open-ended: money launderers split, swap, and bridge funds, cut their
Computer-use agents (CUAs) are commonly evaluated against fixed task specifications, but users may omit requir
Command-line interface (CLI) agents increasingly execute longer-horizon tasks, yet existing benchmarks either
Many Indian banks serve customers through FAQ pages and scripted chatbots. Assistants based on language models