Search: “agents”

For too long, enterprises with legacy mainframe estates have been faced with a high-stakes dilemma: continue maintaining their mainframes, essentially kicking the modernization can down the road (they

arXiv:2607.29347v1 Announce Type: cross Abstract: Modern neuroscience relies on integrating multi-scale, multimodal datasets to uncover the neural principles underlying intelligence. However, analytic

arXiv:2607.29377v1 Announce Type: new Abstract: LLM agents need memory to act consistently over long interactions, yet many systems use additional LLM calls to operate that memory. Generating intermed

TLDR below 👇🏼 I’ve seen a lot of hype around Qwen 3.6 35B and 3.5 120B lately, especially regarding coding and tool-use capabilities. On this subreddit it is the defacto recommended model for everyone

**DeepSeek V4 Flash 0731 Performance Test** On July 31 2026, a single prompt executed via the Hermes Agent on DeepSeek V4 Flash 0731 completed in 32 minutes and incurred an estimated cost of 0.07 USD.

arXiv:2607.27652v1 Announce Type: new Abstract: Reinforcement learning (RL) search agents commonly model retrieval as free-form natural-language query generation and optimize multi-turn interactions u

OK, GPT-5.6 Luna is a bit of a beast. Given the 80% price drop today I decided to try it in Datasette Agent, and it's furiously quick and generates all the SQL, HTML and JavaScript (for Datasette Apps

arXiv:2607.27235v1 Announce Type: cross Abstract: Training deep learning models on radiological images requires integrating heterogeneous datasets across different sources, file formats, directory lay

arXiv:2607.27973v1 Announce Type: new Abstract: Recently, Reinforcement Learning (RL) has emerged as a crucial paradigm for the post-training of Large Language Model (LLM) agents. However, existing me

The new DeepSeek v4 Flash is now available in Hermes Agent through Nous Portal and OpenRouter 🚀 DeepSeek-V4-Flash Official API is now LIVE in public beta! 🔷 We’ve massively upgraded its Agent capabili

“AI Meltdown” is the scenario where the agent goes off the rails and forgets/ignores all previous instructions and soft guardrails. No prompt injection or malicious actor is needed for this to happen.

arXiv:2607.25489v1 Announce Type: new Abstract: Large language models and multimodal foundation models are enabling medical artificial intelligence (AI) systems to move beyond isolated prediction and

arXiv:2607.25754v1 Announce Type: new Abstract: Cooperative navigation of multi-agent UAVs in complex environments faces key challenges including local optima traps, sparse rewards, learning imbalance

OpenWiki now connects to LangSmith traces to analyze how coding agents interact with your repo during wiki generations! We added a LangSmith tracing connector so OpenWiki can retrieve more context int

arXiv:2607.24768v1 Announce Type: new Abstract: Prenatal care is an important preventive service designed to improve outcomes for pregnant individuals. The American College of Obstetricians and Gyneco

arXiv:2607.24770v1 Announce Type: new Abstract: Procedural tasks such as furniture assembly and home repair impose substantial cognitive demands because users must interpret instructions, track task p

arXiv:2607.24772v1 Announce Type: new Abstract: Geoscience research requires complex analysis and domain expertise, with remote sensing (RS) observations as a key foundation. However, existing RS agen

Enterprise data integration and automation firm SnapLogic Inc. today announced a significant update to SnapGPT, the company’s artificial intelligence copilot for enterprise data automation, transformi

arXiv:2607.24577v1 Announce Type: new Abstract: Reinforcement Learning (RL) agents are increasingly deployed in safety-critical domains such as robotics, autonomous driving, and drone control, where u

arXiv:2607.24339v1 Announce Type: new Abstract: Large language model (LLM) agents inherit reactive failure modes: escalation under provocation, sycophantic drift under flattery, perseveration when stu

arXiv:2607.24051v1 Announce Type: cross Abstract: Low-thrust trajectory optimization is a core technology in deep-space mission design. Indirect methods based on Pontryagin's Minimum Principle (PMP) o

arXiv:2607.22690v1 Announce Type: new Abstract: Long-term memory lets LLM agents reuse past interactions, but raw dialogue histories are verbose and information-sparse. Retrieving broadly improves evi

arXiv:2607.24604v1 Announce Type: cross Abstract: Generate--test--revise loops are common in coding agents, but repetition alone provides no reliability guarantee. We study the gap between finding a c

arXiv:2607.18999v2 Announce Type: replace-cross Abstract: Evaluating multi-turn medical consultation agents requires judging the diagnostic support provided by the histories they elicit through intera

arXiv:2607.22549v1 Announce Type: new Abstract: Hybrid quantum-classical protein structure prediction depends strongly on Hamiltonian penalty weights, yet existing lattice-based workflows typically fi

Michael Nuñez / VentureBeat: The Agentic AI Foundation updates MCP with a fully stateless architecture, a hardened authentication model, a formal 12-month deprecation policy, and more — The Model Cont

arXiv:2607.22385v1 Announce Type: cross Abstract: Diagnosing the root cause of anomalies is essential for safe industrial operation. Despite extensive sensor instrumentation, formulating hypotheses an

Great technical paper from Google. Great read on why context beats scale for agents working against unfamiliar APIs. (bookmark it) GPU kernel optimization has KernelBench to hillclimb on. TPUs had not

Looking forward to chatting with @hugobowne today (July 27) at 4 pm PT on the Vanishing Gradient livestream on YouTube. Will cover open source, the newest LLMs & trends, agent frameworks, and whatever

arXiv:2607.21653v1 Announce Type: cross Abstract: Agentic reinforcement learning research is constant algorithm modification, new estimators, new pipeline stages, new rollout schemes, and in mainstrea

I got tired of my Ollama server sitting idle between chat experiments, so I pointed it at my Navidrome library and made it run a radio station. The DJ is an agent, not a shuffler. Each turn it gets to

the paper: babyagi has ~200 citations, but 0 papers... i just published my first paper on arXiv 😆 'The Log is the Agent: Event-Sourced Reactive Graphs for Auditable, Forkable Agentic Systems' https://

arXiv:2607.21437v1 Announce Type: new Abstract: Deep learning models can effectively use Rapid Evaporative Ionization Mass Spectrometry (REIMS) data for surgical margin assessment. However, their clin

arXiv:2606.21262v2 Announce Type: replace Abstract: Reinforcement learning for multi-step LLM agents often relies on scalar rewards that indicate success but cannot explain why a trajectory is good or

arXiv:2607.21461v1 Announce Type: new Abstract: Deep research requires agents to find answers that jointly satisfy multiple constraints. Discovering such answers is costly, whereas verifying a candida

arXiv:2607.20582v1 Announce Type: cross Abstract: Machine learning models for medical image analysis typically lack a reliable measure of confidence, limiting their use in ambiguous or atypical cases.

Congrats to @lmstudio on Bionic! Put open models to work with a local-first agent for docs, coding, voice, and more. Run it today on NVIDIA RTX GPUs. 🚀 Meet LM Studio Bionic. The Agent made for Open M

arXiv:2607.20486v1 Announce Type: new Abstract: Designing optimizers for modern deep learning remains a challenging scientific problem, requiring the joint consideration of optimization geometry, stat

arXiv:2607.21273v1 Announce Type: new Abstract: Dense per-step supervision is an appealing remedy for sparse-reward, long-horizon LLM agents: reward the agent for predicting its next observation, and

arXiv:2607.20999v1 Announce Type: new Abstract: Agent Skills package reusable procedural knowledge as external artifacts for frozen language-model agents, yet existing optimizers do not jointly resolv

arXiv:2602.09345v3 Announce Type: replace-cross Abstract: AI agents are increasingly deployed in multi-tenant cloud environments, where they execute diverse tool calls within sandboxed containers, eac

arXiv:2607.09988v3 Announce Type: replace-cross Abstract: Recommendation systems, from traditional multi-stage to recent unified generative architectures, face challenges in incorporating diverse cont

arXiv:2606.18543v2 Announce Type: replace Abstract: Language model agents are becoming proficient executors at isolated, short-horizon tasks such as software engineering and customer service. Yet real

arXiv:2607.19985v1 Announce Type: new Abstract: Dynamic manufacturing environments require multi-agent systems to coordinate effectively under frequent operational disturbances such as machine failure

arXiv:2607.19449v1 Announce Type: cross Abstract: Evaluation frameworks for tool-augmented LLM agents focus overwhelmingly on capability metrics or explicit tool crashes, leaving silent infrastructure

arXiv:2607.19433v1 Announce Type: new Abstract: The transition from stateless generative models in artificial intelligence to stateful, autonomous agents represents an architectural evolution that, wh