Search: “agents”

arXiv:2607.07368v1 Announce Type: cross Abstract: AI control is a family of techniques to prevent an AI with malicious goals from subverting its operator's intent. AI Control usually studies a single

arXiv:2607.06614v1 Announce Type: cross Abstract: Accurate station-level demand forecasting is essential for the efficient operation of bike-sharing systems, yet it remains challenging due to complex

arXiv:2607.06413v1 Announce Type: cross Abstract: Large language model coding agents increasingly perform open-ended data modeling and analysis. These agents are stochastic and adaptive, and therefore

dcode <> nemotron 3 ultra <> OpenShell 🔥 Never been easier to own your agent IP! Introducing the NemoClaw Deep Agents Blueprint, a reference architecture for building open agent systems developed with

arXiv:2607.05477v1 Announce Type: cross Abstract: Improving the task performance of Large Language Models (LLMs) is essential, yet scaling these models faces significant challenges such as diminishing

Supply chain artificial intelligence startup DeepFabric today announced the general availability of an AI agent platform built for supply chain execution, and a roster of enterprise customers is alrea

arXiv:2607.05844v1 Announce Type: new Abstract: Agent systems accumulate conflicting observations across branches, retries, and replicas, yet many practical memory layers still collapse disagreement b

arXiv:2607.05482v1 Announce Type: cross Abstract: Large language models (LLMs) can plan behavior for embodied agents from natural language, but treating the LLM as a request/response oracle on the cri

arXiv:2607.01469v2 Announce Type: replace Abstract: Agentic Video Question Answering (VideoQA) systems invoke tools during inference, but their tool libraries are fixed, so recurring procedures are re

arXiv:2602.21534v3 Announce Type: replace Abstract: Agentic reinforcement learning (ARL) has rapidly gained attention as a promising paradigm for training agents to solve complex, multi-step interacti

arXiv:2607.02703v1 Announce Type: cross Abstract: In this paper, we describe LLMoxie, an institutional AI platform whose three-tiered architecture supports multi-cloud and on-premise inference, a Lite

arXiv:2509.23960v2 Announce Type: replace-cross Abstract: Co-optimizing safety and performance in large-scale multi-agent systems remains a fundamental challenge. Existing approaches based on multi-ag

Harrison Chase argues that evaluations (evals) are the most intellectually demanding aspect of agent engineering, distinguishing them from other engineering tasks that may be more routine or formulaic

arXiv:2607.05346v1 Announce Type: new Abstract: We propose OptiAgent, a multi-agent framework that, given a natural language description of an Operations Research problem, is able to output a solver-r

Application and network security company Radware Ltd. today expanded its Agentic AI Protection product with compliance reporting, deeper visibility into artificial intelligence agent activity, and new

arXiv:2607.03423v1 Announce Type: cross Abstract: Modern AI agent implementations such as frontier coding agents chain multiple tools at runtime that create a security surface that per-tool guardrails

arXiv:2603.23483v2 Announce Type: replace-cross Abstract: Agentic multimodal large language models (MLLMs) (e.g., OpenAI o3 and Gemini Agentic Vision) achieve remarkable reasoning capabilities through

arXiv:2607.04235v1 Announce Type: new Abstract: Large language model agents operate in partially observable, long-horizon settings where obtaining supervision remains a major bottleneck. We address th

The year 2026 could be remembered as the moment when storage technology received a massive promotion. The reason is that the current transition from simple chatbots to agentic AI systems has raised th

arXiv:2607.04708v1 Announce Type: cross Abstract: Agentic AI is shifting online shopping from search toward delegated purchasing, where autonomous buying agents monitor markets and decide when to buy

arXiv:2503.20666v2 Announce Type: replace-cross Abstract: Thematic analysis (TA) is a widely used qualitative approach for uncovering latent meanings in unstructured text data. TA provides valuable in

arXiv:2607.04034v1 Announce Type: cross Abstract: The language models that underpin agents have seen a rapid rise in performance on function calling benchmarks. However, the metrics used in the traini

Vercel has announced the availability of Agent Runs in both the Vercel MCP (Model Context Protocol) and CLI (Command Line Interface), expanding developer capabilities for AI-powered automation and dep

arXiv:2602.19127v2 Announce Type: replace Abstract: With the rapid advancement of agent-based methods in recent years, Agentic RAG has undoubtedly become an important research direction. Multi-hop rea

arXiv:2607.01846v1 Announce Type: new Abstract: Domain agents often face noisy business data, uncertain post-training gains, offline/application mismatch, and adapter-release risk. This paper presents

arXiv:2607.02116v1 Announce Type: new Abstract: Autonomous AI agents increasingly depend on external knowledge stores, yet most retrieval pipelines provide relevance without durable guarantees of prov

arXiv:2501.07892v2 Announce Type: replace-cross Abstract: Large language models (LLMs) have shown strong performance in automated code generation, with few-shot prompting widely used for its simplicit

arXiv:2607.01793v1 Announce Type: new Abstract: LLM agents increasingly perform autonomous actions through external tools, leading to complex and evolving safety risks. However, existing safety testin

arXiv:2607.00502v1 Announce Type: new Abstract: While long-horizon mobile GUI agents typically rely on thought-action-observation loops, they struggle to separate persistent task states from transient

arXiv:2607.01034v1 Announce Type: cross Abstract: Large language model (LLM)-based conversational agents (CAs) are now ubiquitous, creating new opportunities for AI-mediated behavior change. Their cap

arXiv:2607.01087v1 Announce Type: cross Abstract: Generative AI is shifting software engineering from a practice organized around scarce implementation effort toward one organized around abundant, low

arXiv:2607.00233v1 Announce Type: new Abstract: How do two agents invent a shared language from scratch? In a Lewis signaling game, a sender and receiver must coordinate on a code using only their int

arXiv:2607.00011v1 Announce Type: cross Abstract: Reusable skill libraries are becoming important infrastructure for large language model (LLM) agents, yet existing selection methods often treat skill

arXiv:2606.31182v1 Announce Type: new Abstract: Recent work shows that LLM agents can improve sharp-constant inequalities by searching for extremal constructions, which yield upper bounds. We address

arXiv:2603.26266v3 Announce Type: replace Abstract: Large vision-language models have endowed GUI agents with strong general capabilities for interface understanding and interaction. However, due to i

Harrison Chase suggests using a wiki structure as the foundation for building AI agents with memory systems, citing its simplicity and extensibility as key advantages. This approach would organize age

if you want agents to do work at scale (like security triage, trace analysis, document parsing), they need structured workflows enforced w/ code map reduce is a great example -- exactly the kind of pa

arXiv:2606.31504v1 Announce Type: new Abstract: We present SimpleSearch-VL, an efficient, reliable, and practical framework for multimodal agentic search. Its core idea is to improve the agent's own s

Together AI presented a 2-hour technical deep dive on building inference engines capable of handling trillion-token agentic workloads, covering architecture and optimization strategies for large-scale

Couchbase Inc. is trying to solve one of the hardest problems in enterprise artificial intelligence today: turning brittle, chat-style pilots into production-grade agents capable of remembering, reaso

arXiv:2606.30296v1 Announce Type: new Abstract: Multi-round reflection lets agents built on large language models recover from failures within a single task, but each task remains an isolated episode:

arXiv:2603.05786v2 Announce Type: replace-cross Abstract: As AI agents become widely deployed as online services, users often rely on an agent developer's claim about how safety is enforced, which int

arXiv:2606.28971v1 Announce Type: new Abstract: Real-world image restoration (IR) remains challenging due to complex and coupled degradations. While recent agentic IR frameworks leverage Large Languag

Semantic search alone doesn't cut it. Neither does brute-force grep. Agents need both. Today we're shipping the Retrieval Harness in LlamaParse Index: semantic search, server-side grep, and file-level

arXiv:2606.14397v2 Announce Type: replace Abstract: As agentic systems continue to evolve and are widely deployed in real-world scenarios, there is a growing demand to faithfully evaluate their capabi

arXiv:2606.26400v1 Announce Type: new Abstract: Agentic systems are changing how complex operational tasks are coordinated, introducing a new paradigm for connecting heterogeneous data sources and aut