agents

arXiv:2605.23459v1 Announce Type: cross Abstract: Enterprise AI systems, built on large language models, retrieval pipelines and autonomous agents, introduce a class of risks that traditional software

As enterprises confront spiraling cloud inference bills, on-prem AI computing is emerging as the decisive lever for making agentic AI economically viable at scale. Dell Technologies Inc.’s announcemen

arXiv:2605.23165v1 Announce Type: cross Abstract: Autonomous robotic exploration of unknown and hazardous environments, a long-standing challenge, can be significantly improved by leveraging the advan

arXiv:2605.23204v1 Announce Type: new Abstract: Scientific research is being reshaped by AI systems that move beyond isolated assistance toward longer-horizon workflows spanning literature grounding,

arXiv:2605.23590v1 Announce Type: new Abstract: ReAct-style agents for search-intensive, multi-step reasoning tasks rely largely on their own internal judgment to decide what evidence to seek, which r

arXiv:2605.23372v1 Announce Type: cross Abstract: In curriculum reinforcement learning (CRL), an agent incrementally accumulates knowledge over a sequence of tasks (i.e., a curriculum), and the learni

arXiv:2605.23271v1 Announce Type: cross Abstract: The rapid evolution of generative video foundation models has propelled the field toward professional-grade cinematic synthesis. To achieve such deman

arXiv:2605.22905v1 Announce Type: new Abstract: Self-evolving agents should not train on examples they cannot justify. Data-free self-evolving search agents offer a scalable route to systems that gene

arXiv:2605.23653v1 Announce Type: new Abstract: Timely and transparent feedback is essential for effective surgical training, yet current assessment remains dependent on expert observation, limiting s

arXiv:2605.23899v1 Announce Type: new Abstract: Language agents increasingly improve by reusing skills -- structured procedural artifacts distilled from past experience. In particular, domain-level an

arXiv:2605.22897v1 Announce Type: new Abstract: A persistent challenge in machine learning for scientific applications is jointly achieving prediction and understanding. Statistical models excel on st

arXiv:2605.22868v1 Announce Type: new Abstract: Autonomous systems and smart-industry deployments increasingly split computation across near-sensor, edge, and cloud resources, where tight energy, late

arXiv:2605.23327v1 Announce Type: new Abstract: Lane detection stands as a crucial perception task in autonomous driving and advanced driver assistance systems. However, existing methods still degrade

/goal is really insane! It's how you can get the most out of coding agents today. For efficiency, I find it works best when you do planning before /goal. This ensures the agent has the right context a

arXiv:2602.00979v2 Announce Type: replace-cross Abstract: Large language models (LLMs) are increasingly deployed as educational agents for automatic short answer grading (ASAG) in real-world education

This article defines and clarifies key terminology related to AI agents, including the concepts of 'harness' and 'scaffold,' which are important architectural and operational components in building an

(I'm firmly on team red/green TDD for agent code, I like having a test suite that protects against them breaking old features when they make new changes - https://simonwillison.net/guides/agentic-engi

Nous Research is inviting developers and enthusiasts to participate in a 'Hermes Agent Jam' event scheduled for Wednesday, likely a hackathon or collaborative workshop focused on building or improving

arXiv:2605.22825v1 Announce Type: cross Abstract: Key Value Indicators (KVIs) provide a decision oriented view of a service by summarizing how operational performance translates into stakeholder value

arXiv:2511.02239v2 Announce Type: replace-cross Abstract: Learning generalizable policies for robotic manipulation increasingly relies on large-scale models that map language instructions to actions (

arXiv:2605.22863v1 Announce Type: new Abstract: LLM agents today communicate via text, which incurs considerable latency and information loss due to the need to autoregressively decode the sharer mode

arXiv:2603.10688v2 Announce Type: replace-cross Abstract: Autonomous vehicles rely on map information to understand the world around them. However, the creation and maintenance of offline high-definit

arXiv:2605.22949v1 Announce Type: new Abstract: Foundation model agents increasingly operate in multi-agent deployments where a coordinator must decide which agent's response to trust. The standard ap

arXiv:2605.23723v1 Announce Type: new Abstract: Large language model agents increasingly rely on persistent memory to store past interactions, retrieve relevant demonstrations, and improve long-horizo

arXiv:2605.23350v1 Announce Type: new Abstract: Autonomous exploration of multi-floor buildings remains challenging for ground robots because conventional 2D and 2.5D maps cannot represent overlapping

arXiv:2602.13473v2 Announce Type: replace Abstract: Although foundation models have demonstrated remarkable success in general domains, the application of these models to electroencephalography (EEG)

New paper from Microsoft on Self-Evolving Agent Skills New research from Microsoft Research I see a lot of AI engineers handwriting agent skill docs and hope they generalize. Probably not optimal. Thi

nice write up from the HuggingFace folks aggregating works on defining agents, harnesses, environments, RL, etc. The more we can roughly have a shared vocabulary the better…I still find it confusing (

Plugins can also affect the empty state of the new menu - the latest datasette-agent adds a form for kicking off a new agent conversation - live demo (if you sign in with GitHub) on https://agent.data

arXiv:2605.22834v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) systems depend critically on document chunking quality for retrieving relevant context. Fixed chunking segments doc

Ralph Loops are powerful, but wrapping a naive loop in a shell script is a total token burner in production. Pinecone Principal Engineer Jen Hamon breaks down why standard loops collapse: ❌ The Bug: P

arXiv:2605.23179v1 Announce Type: new Abstract: Agentic AI orchestrators reduce the interface and assembly costs of composing information systems capabilities across organizational boundaries, seeming

arXiv:2605.23406v1 Announce Type: new Abstract: End-to-end autonomous driving solutions, which directly process multimodal sensory data and output fine-grained control commands, have gradually become

arXiv:2605.22997v1 Announce Type: new Abstract: In autonomous driving, mapping is critical for motion planning but remains an under-utilized resource for perception tasks such as 3D object detection.

arXiv:2605.23832v1 Announce Type: new Abstract: Deploying heterogeneous multi-agent robot fleets for collaborative perception requires robust data exchange and scalable software architectures. However

arXiv:2605.23426v1 Announce Type: cross Abstract: Socially fluent agentic AI can now participate in online interaction in ways that resemble ordinary human conversation, potentially weakening people's

arXiv:2602.01665v2 Announce Type: replace-cross Abstract: The design of environments plays a critical role in shaping the development and evaluation of cooperative multi-agent reinforcement learning (

arXiv:2605.23257v1 Announce Type: cross Abstract: Navigating under non-stationary environment shifts poses a critical challenge for a Vision-and-Language Navigation (VLN) agent deployed in the wild. Y

arXiv:2605.23278v1 Announce Type: new Abstract: Language models trained on observed sequences are often described as learning the conditional distribution of the next token given previous tokens. This

arXiv:2605.23414v1 Announce Type: new Abstract: LLM-based multi-agent systems can fail even when planned actions are executed correctly because agents may misjudge their knowledge when evaluating plan

arXiv:2511.00266v2 Announce Type: replace Abstract: Accurate trajectory prediction is crucial for safe and reliable autonomous driving systems, requiring models that capture long-term temporal depende

Release: datasette-agent 0.1a4 Taking advantage of the new makeJumpSections() JavaScript plugin hook added in Datasette 1.0a30, datasette-agent now presents this 'Start a new agent chat' interface as

Grok Build sub-agent swarm weekend fun. You can reuse the prompt for your projects: Read the proof of `https://cdn.openai.com/pdf/74c24085-19b0-4534-9c90-465b8e29ad73/unit-distance-proof.pdf` and come

I asked my eng team if I could ship code to prod They told me no 💀 CEOs are uniquely prone to AI psychosis because they’re sufficiently distant from the last mile of work that still has to happen to g

Please for the love of god don’t take this to heart Go out, have fun, make friends, touch some grass. You can work as hard as you want when you’re back. kinda fascinating that “going out” became a kin

Yohei Nakajima expresses the overwhelm of having numerous experimental ideas he wants to pursue, reflecting on the challenge of prioritization and resource constraints in AI research and development.