Category
14,562 papers
CoMemBench is introduced, an execution-grounded benchmark for collaborative memory sharing and isolation across multi-agent workflow topologies, and reveals a sharing-isolation trade-off: broader context improves information availability but can weaken isolation, while system rankings shift across topologies and artifa...
The contribution is not a new fixed-point calculus, but a characterization of when proposal--history correlation at the model--tool boundary is necessary for certification, separating indefinite operational viability from finite worst-case verified progress.
The Noisy Test-time Reinforcement Learning framework (NTRL-Code) is proposed, which enables robust self-evolution of code LLMs using only unlabeled noisy data during the testing stage, and employs an abstract-syntax-tree (AST)-based structural aggregation mechanism to estimate a proxy target from multiple candidate pro...
Running GUI agents on edge devices can keep sensitive screens and interaction histories local, but the computational cost of inference at every action step makes deployment challenging. Existing GUI agent systems either perform full vision-language model (VLM) inference at each action step or reuse coarse-grained knowl...
Reach audiences
Advertise in front of researchers, engineers, and readers.
Time-series diagnostic systems rarely rely on retrieving relevant historical cases, and when they do, retrieval is evaluated only indirectly through downstream prediction. We introduce READ-Bench, a benchmark for historical-case retrieval across 12 diagnostic datasets, centered on multivariate time series, that defines...
A simple barrier model is introduced where each prompt has a baseline safety level and each augmentation a random thermally activated barrier determines the entire ($N, M$) attack surface.
Recurrent state provides a complementary carrier of workspace content, whose recovery, persistence and causal uses require separate measurements, and sign-guarded steering, which improves target top-five success over coordinate exchange on matched verbal-report trials in five models.
GameBoyWorlds is introduced, a testbed for agentic self-improvement in video games and it is shown that contemporary approaches to self-improvement are lacking, with world modelling and autonomous skill discovery failing, and a novel strategy that uses curiosity-based exploration to write guides achieving only partial...
AI agents are stateless across sessions by default and therefore operationally amnesic: each session begins with little durable knowledge of prior failures, repairs, preferences, or successful strategies. As a result, agents repeat the same mistakes and discard hard-won experience. The dominant fix is \emph{bespoke mem...
The PAU (Python API Understanding) benchmark is introduced, where models are provided with black-box, API-level access to code snippets, and inspiration is taken from the Asymmetric Actor Critic paradigm, frequently used in robot learning, to post-train models for interactive code understanding.
This work proposes an AI safety framework that binds worker agents to contracts specifying their permitted actions, and shows how these contracts can be enforced and specified by assigning distinct responsibilities to monitor agents and judges, and asymmetric computational resources to monitors and workers.
The proposed EngramRAG is an adaptive memory architecture coupling a low-latency Waking State reflex with an asynchronous background Dreaming State consolidation cycle, and introduces triple-source hybrid retrieval fusing dense vectors, BM25, and U-PPR via dynamic Reciprocal Rank Fusion (RRF).
Machine-learning networks can learn without detailed instructions from a designer. Those that do may offer insight into how the brain reorganizes itself during learning.
Announcing Gemini 4 Argon, our frontier model for real-world coding, enterprise knowledge work and cyber defense, rolling out soon.
With $2.1 million funding from Google.org, the open-source Public Transit Intelligence Hub will unify public transit monitoring, operations, and passenger communication.
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Professor Sherry Turkle’s new book, “Artificial Intimacy,” offers a withering critique of chatbots and the antisocial dynamics she believes they encourage.
Machine Intelligence
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
