Autonomous agents, tool use, and agentic systems
Last week, a team from Stanford and UCSF (Asadi, O'Sullivan, Fei-Fei Li, Euan Ashley et al.) dropped two companion papers. The first, MAR...
I've been experimenting with multi-agent AI systems and ended up building something more ambitious than I originally planned: a fully ope...
I've been sitting with a question for a while: what happens when AI agents aren't just tools to be used, but participants in an economy? ...
![[2602.21340] HiPPO Zoo: Explicit Memory Mechanisms for Interpretable State Space Models](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
The paper introduces the HiPPO Zoo, a framework enhancing state space models with explicit memory mechanisms for improved interpretabilit...
This paper presents an efficient algorithm for opportunistic approachability, improving upon previous methods by achieving faster approac...
The paper presents Tool-R0, a framework for training self-evolving LLM agents capable of tool-learning without prior data, showcasing sig...
The paper presents cVMDx, an advanced diffusion model for multimodal highway trajectory prediction, enhancing efficiency and accuracy in ...
The paper proposes a new method for evaluating AI models using robust lotteries, addressing limitations of traditional pairwise compariso...
The paper discusses vulnerabilities in AI control protocols, specifically how Agent-as-a-Proxy attacks can bypass existing monitoring def...
The paper introduces xMemory, a novel approach to agent memory systems that enhances retrieval by decoupling and aggregating semantic com...
The paper introduces LatentLens, a method for mapping visual tokens to natural language descriptions in Vision-Language Models (VLMs), en...
The OGD4All framework enhances citizen interaction with geospatial Open Government Data using Large Language Models, achieving high accur...
The paper presents RebuttalAgent, a framework using Theory of Mind for strategic persuasion in academic rebuttals, addressing the complex...
The paper presents FigEx2, a framework for detecting and captioning panels in scientific compound figures, enhancing understanding and ac...
This article explores the gaps in understanding superintelligence misalignment, emphasizing the absence of the human subject and the impl...
This article presents a unified framework for Aerial Vision-Language Navigation (VLN), enabling UAVs to interpret natural language and na...
The paper presents KD-OCT, a novel knowledge distillation framework that enhances the efficiency of deep learning models for classifying ...
This article presents SORL, a novel approach to stabilize off-policy training for long-horizon LLM agents, addressing issues of instabili...
This paper presents a proof of learning rate transfer in linear multi-layer perceptrons (MLPs) using a new parameterization method called...
The paper presents Cosmos-Predict2.5, an advanced model for world simulation in Physical AI, integrating various generation methods and i...
The paper introduces SPACeR, a framework for enhancing autonomous vehicle behavior through self-play reinforcement learning anchored by a...
The paper introduces FML-bench, a new benchmark for evaluating machine learning agents in scientific research, focusing on exploration di...
The paper presents SLM-MUX, a novel architecture for orchestrating small language models (SLMs) to improve reasoning accuracy, achieving ...
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