agents

arXiv:2510.20036v2 Announce Type: replace Abstract: Large language model (LLM) agents rely on external tools to solve complex tasks, but real-world toolsets often contain redundant tools with overlapp

arXiv:2605.09366v1 Announce Type: new Abstract: Transforming neuroimaging data into clinically actionable biomarkers is a knowledge-intensive and labor-intensive process. Standardized workflows such a

arXiv:2605.10257v1 Announce Type: new Abstract: Managing disruptions in railway traffic management is a major challenge. Rising traffic density and infrastructure limits increase complexity, making th

arXiv:2409.13107v3 Announce Type: replace Abstract: Large language model-based (LLM) agents are emerging as a powerful enabler of robust embodied intelligence due to their capability of planning compl

arXiv:2605.08830v1 Announce Type: cross Abstract: End-to-end autonomous driving requires models to understand traffic scenes, infer driving intent, and generate executable motion plans. Recent vision-

arXiv:2605.10106v1 Announce Type: cross Abstract: Recent advances in Multi-modal Large Language Models (MLLMs) target 3D spatial intelligence, yet the progress has been largely driven by post-training

Voice selection significantly impacts user perception and experience across various applications, including financial services support, healthcare intake processes, and entertainment platforms. Togeth

we just shipped delta channels in langgraph 1.2. as agents run longer and use more context, full-state checkpointing doesn't scale, but delta channel snapshots do. this new algorithm is now powering m

arXiv:2605.08310v1 Announce Type: cross Abstract: Browser agents are increasingly deployed in long-horizon tasks, which require executing extended action chains to accomplish user goals. However, this

arXiv:2605.08380v1 Announce Type: cross Abstract: AI agents are increasingly framed as software-engineering teammates, yet most research studies them inside human-centered workflows. Little is known a

What’s special about the @LangChain community is that it’s built by those who are willing to take the extra step to push the boundaries of what’s possible. It’s a community that builds technologies th

arXiv:2602.06286v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in high-stakes settings where good decisions require forming beliefs over the probability of

arXiv:2605.08460v1 Announce Type: cross Abstract: Since the official release of ChatGPT in 2022, large language models (LLMs) have rapidly evolved from chatbot-style interfaces into agentic systems th

arXiv:2605.08478v1 Announce Type: new Abstract: We study how to allocate inference-time compute for competitive programming under fixed budgets. Evaluating 216 Codeforces problems across Divisions 1-3

arXiv:2603.23806v2 Announce Type: replace-cross Abstract: AI agents are increasingly embedded in real software systems, where they execute multi-step workflows through multi-turn dialogue, tool invoca

arXiv:2605.09650v1 Announce Type: new Abstract: Modern agents built on frontier language models often cannot adapt their weights. What, then, remains trainable? We argue it is the agent's workspace, t

This post analyzes the strategic directions and priorities of OpenAI, Anthropic, and xAI by examining their publicly listed job openings, inferring each company's focus areas, capabilities development

arXiv:2508.11070v2 Announce Type: replace Abstract: Decision makers are increasingly relying on machine learning in sensitive situations. Algorithmic recourse aims to provide individuals with actionab

arXiv:2605.08450v1 Announce Type: cross Abstract: Imitation learning is effective for training agents when expert demonstrations are available, but collecting demonstrations for every complex task in

arXiv:2605.08084v1 Announce Type: cross Abstract: The pursuit of autonomous driving has produced one of the richest sensor data collections in all of robotics. However, its scale and diversity remain

arXiv:2605.06976v1 Announce Type: cross Abstract: Many ranking and agent trace datasets are recorded as linear orders even though their latent structure is only partially ordered. This is especially c

A lab with no humans🧪 Tokyo University of Science is operating a robotic medical research laboratory equipped with 10 robots, including the humanoid robot Maholo LabDroid, developed by the Tokyo Insti

arXiv:2508.15294v4 Announce Type: replace Abstract: In the current field of agent memory, extensive explorations have been conducted in the area of memory retrieval, yet few studies have focused on ex

arXiv:2605.06737v1 Announce Type: cross Abstract: Autonomous agents based on Large Language Models (LLMs) are increasingly being utilized in complex software systems. However, reliability remains a si

arXiv:2605.05703v2 Announce Type: replace-cross Abstract: Optimizing the communication structure of large language model based multi-agent systems (LLM-MAS) has been shown to improve downstream perfor

Agent engineering is hard Deep Agents hides a lot of the weird systems complexity, but still gives you more room to customize the harness than almost any agent SDK I've used This is harder to build th

arXiv:2605.06713v1 Announce Type: cross Abstract: Agentic AI systems can plan, call tools, inspect code, interact with web applications, and coordinate multi-step workflows. These same capabilities ch

Ben Thompson / Stratechery: Agentic inference is set to be different than today's inference, and will change compute infrastructure because speed won't matter when humans aren't involved — Subscribe t

arXiv:2512.10371v2 Announce Type: replace Abstract: The rapid development of mobile GUI agents has stimulated growing research interest in long-horizon task automation. However, building agents for th

# Agents as Products This post likely explores how AI agents can be effectively deployed as standalone products, discussing their practical applications and advantages over traditional software soluti

arXiv:2602.04672v3 Announce Type: replace Abstract: Reconstructing dynamic hand-object interactions from monocular videos is critical for dexterous manipulation data collection and creating realistic

arXiv:2605.06841v1 Announce Type: new Abstract: In model-based learning, the agent learns behaviors by simulating trajectories based on world model predictions. Standard world models typically learn a

arXiv:2605.07744v1 Announce Type: new Abstract: The concurrent target assignment and pathfinding (TAPF) problem extends multi-agent pathfinding (MAPF) by asking planners to allocate distinct targets a

Enterprise AI adoption has crossed a threshold: The question is no longer whether to invest, but how to do it wisely. As agentic workloads multiply and inference costs rise, AI choice — the ability to

An abbreviated history of Cognition... Scott Wu is the co-founder of Cognition AI, one of the fastest-growing companies in history. He’s also the greatest competitive programmer the US has ever produc

arXiv:2509.03736v2 Announce Type: replace Abstract: The impressive capabilities of Large Language Models (LLMs) raise the possibility that synthetic agents can serve as substitutes for real participan

arXiv:2605.07103v1 Announce Type: new Abstract: Reaction feasibility prediction, as a fundamental problem in computational chemistry, has benefited from diverse tools enabled by recent advances in art

arXiv:2512.03476v2 Announce Type: replace-cross Abstract: Bridging the gap between theoretical conceptualization and computational implementation is a major bottleneck in Scientific Computing (SciC) a

arXiv:2605.05583v2 Announce Type: replace Abstract: LLM agents that operate over long context depend on external memory to accumulate knowledge over time. However, existing methods typically store eac

arXiv:2602.17407v2 Announce Type: replace-cross Abstract: Phased-array Bluetooth systems have emerged as a low-cost alternative for performing aided inertial navigation in GNSS-denied use cases such a

arXiv:2605.07605v1 Announce Type: new Abstract: Autonomous robotic assembly of interlocking bricks demands seamless integration of long-horizon task reasoning, spatial grounding, and fine-grained mani

arXiv:2605.06702v1 Announce Type: new Abstract: Large language models (LLMs) have become a central foundation of modern artificial intelligence, yet their lifecycle remains constrained by a rigid sepa

This post from Nous Research discusses the integration of computer use capabilities with Hermes Agent models in collaboration with Claude (CUA), enabling AI agents to interact with computer interfaces

arXiv:2605.06788v1 Announce Type: new Abstract: When multi-agent systems (MAS) fail, identifying where the decisive error occurred is the first step for automated recovery to an earlier state. Error a

arXiv:2603.02274v2 Announce Type: replace-cross Abstract: Precision oncology is currently limited by the small-N, large-P paradox, where high-dimensional genomic data is abundant but pharmacological r

Cool paper from PwC. 'Earlier is always better' is the default intuition for agent clarification. New paper claims that's mostly wrong. Goal clarification loses nearly all of its value after just 10%