Search: “agents”

arXiv:2604.09482v1 Announce Type: new Abstract: Reasoning in knowledge-intensive domains remains challenging as intermediate steps are often not locally verifiable: unlike math or code, evaluating ste

@hwchase17 I think harness/managed agents is a way for Anthropic to keep its Moat. As models get mature, the need for cloud LLMs might reduce and local LLM models might increase (save cost) and thus t

The search did not return the specific Reddit post. However, result index 2 appears to be a closely related article on the same topic. Let me use what's available to craft an accurate summary based...

arXiv:2604.06562v1 Announce Type: new Abstract: Small language models (SLM) are increasingly used as interactive decision-making agents, yet most decision-oriented evaluations ignore emotion as a caus

I care because understanding which index helps me understand things like what I need to submit content for crawling to, what search agents I should allow in robots.txt, how frequently I can expect the

Mornings feel different lately. Before I even get organized, I already have 5+ agents running. Same thing before I go to sleep. Claude Code, ChatGPT, Qodo, Notion, Linear, NotebookLM. All moving in pa

Secure software supply chain solution provider Chainguard Inc. today unveiled a vulnerability-hunting service that uses frontier artificial intelligence models such as Anthropic PBC’s Claude Mythos 5.

arXiv:2610.18572v1 Announce Type: cross Abstract: Automated post-training transforms pre-trained large language models (LLMs) into models capable of handling diverse domains by automatically construct

Dyna Robotics released **Dyna‑2**, a world‑action language model pre‑trained on more than one million hours of human video, demonstrating new scaling laws across four magnitudes of data. The company f

Ai2 joined COLM 2026 to share advances in open language models, training infrastructure, and AI for science, including Olmo Hybrid, Asta, and Bolmo, while connecting with the broader research communit

arXiv:2610.06650v2 Announce Type: replace Abstract: Wikidata is one of the largest open knowledge bases, yet answering a complex question over it still requires a SPARQL query that names the right ent

AI researchers Zainhas and Parthsareen from Ollama delivered a breakout presentation on October 2, 2026, focusing on evaluating open-source models under real‑world production traffic rather than just

Every time I needed to explore a dataset quickly, the same wall appeared — cleaning boilerplate, encoding errors, deciding which chart actually makes sense. The mechanical parts aren't interesting, th

Generative AI has made remarkable progress in creating increasingly realistic representations of the world. Image models can synthesize photorealistic scenes, video models can generate complex dynamic

arXiv:2609.36892v1 Announce Type: new Abstract: As the capabilities of large language models (LLMs) continue to advance, increasing attention is turning to how to translate their abilities into useful

arXiv:2609.37819v1 Announce Type: cross Abstract: Electronic invoices are replacing paper invoices worldwide, but today's centralized architectures leave three problems unsolved on the consumption sid

arXiv:2609.32569v1 Announce Type: new Abstract: Smart-home assistants are expected to handle diverse, realistic requests that arise in daily life. In such interactions, users often rely on the surroun

arXiv:2609.35432v1 Announce Type: new Abstract: Vision-language-action (VLA) and world-action (WAM) models map observations and instructions directly to robot actions. This directness ties a policy to

arXiv:2609.35576v1 Announce Type: cross Abstract: Large language models are increasingly deployed as stateful assistants that retain information across interactions and use tools to read, modify, and

arXiv:2609.29389v1 Announce Type: new Abstract: Foundation vision-language models (VLMs) understand objects, instructions, and spatial relations, yet translating this capability into robotic manipulat

arXiv:2609.23407v1 Announce Type: cross Abstract: Humans can effortlessly localize the direction of a sound source and integrate it with visual cues for reasoning, yet this remains challenging for emb

arXiv:2609.22090v1 Announce Type: new Abstract: An LLM producing the response pattern associated with a human psychological effect is not the same claim as the LLM possessing that bias. We present Psy

arXiv:2609.19138v1 Announce Type: cross Abstract: Enabling robots to adapt to unfamiliar environments as readily as humans remains a moonshot goal of embodied AI. No finite collection of demonstration

arXiv:2609.10315v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has advanced language-model reasoning in domains such as mathematics and code, where objective a

arXiv:2609.05036v1 Announce Type: new Abstract: AI alignment requires AI systems to adhere to human norms, values, or intentions. Under value pluralism there is no correct target, but a shared prerequ

arXiv:2609.02760v1 Announce Type: new Abstract: On-premise assistants can give factory workers conversational access to machine documentation, but models capable of the task rarely fit shop-floor hard

arXiv:2609.02158v1 Announce Type: cross Abstract: Legal Judgment Prediction (LJP) models are typically trained on documents that describe facts from a prosecutorial perspective. Existing datasets furt

arXiv:2608.29481v1 Announce Type: new Abstract: Pediatric serious illness communication (SIC) is critically important, yet scalable communication training for clinicians remains limited. Compared with

arXiv:2608.27672v1 Announce Type: new Abstract: We present Qwen-GuidePlay-2B, a 2B-parameter language model for dialogue-game interaction. We fine-tune Qwen3.5-2B using three steps: a) SFT on only suc

arXiv:2510.12979v2 Announce Type: replace Abstract: Large language models (LLMs) augmented with multi-step reasoning and action generation abilities have shown promise in leveraging external tools to

arXiv:2603.01113v2 Announce Type: replace Abstract: Interactive task planning with large language models (LLMs) lets robots generate high-level action plans from natural language, but over long horizo

arXiv:2608.24571v1 Announce Type: new Abstract: Tool-augmented language models are bounded by the APIs humans bothered to write; existing tool-creation systems patch this by prompting a frozen LLM at

arXiv:2608.23058v1 Announce Type: new Abstract: Large language models (LLMs) now support forecasting systems that combine language-based reasoning with temporal data, evidence retrieval, external tool

arXiv:2603.02229v2 Announce Type: replace-cross Abstract: Safety post-training has been studied extensively in single-step 'chat' settings where safety typically refers to refusing harmful requests. W

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. Kids outlearn AI—and we still don’t know why Teaching a comput

The next era of AI inference won’t be defined by a single breakthrough chip, network or system. It’ll be defined by how every layer of the AI factory works together. That’s why NVIDIA is extending Ver

arXiv:2608.19794v1 Announce Type: new Abstract: The convergence of large language models (LLMs), structured knowledge bases (KBs), and reasoning ability (RA) presents a promising trajectory toward gen

arXiv:2608.16794v1 Announce Type: cross Abstract: Language and vision-language models generate plausible embodied plans but do not guarantee executability, as their outputs can violate environment dyn

arXiv:2608.10441v1 Announce Type: cross Abstract: Many pipelines can pay a per-example cost to acquire an auxiliary, model-derived observation -- an LLM's structured reasoning, a slow oracle, an expen

Learn how OneAdvanced, a UK enterprise software provider, built a UK-sovereign AI platform by self-hosting Llama 4 Maverick and Llama Guard 4 on Amazon SageMaker AI, with a RAG pipeline on pgvector an

arXiv:2608.08160v1 Announce Type: cross Abstract: The rapid advancement of Large Language Models (LLMs) is revolutionizing AI for Games by enabling open-ended and fluid interactive storytelling. Howev

arXiv:2608.09053v1 Announce Type: cross Abstract: Cardiologists interpret electrocardiograms by localizing waveform components, measuring rhythm and interval patterns, and translating these structured

NVIDIA Nemotron 3.5 Lightning is an open‑source mixture‑of‑experts language model totaling 30 B parameters with only 3 B active during inference, designed to serve high‑volume, low‑latency execution f

arXiv:2608.09574v1 Announce Type: new Abstract: LLMs are rapidly embedding themselves into daily life: drafting our emails, managing our schedules, and making decisions on our behalf. As they move fro

arXiv:2608.06108v1 Announce Type: new Abstract: Investment competence is inherently personalized: the same market evidence can justify different actions for investors with different goals, horizons, p

arXiv:2607.26594v1 Announce Type: cross Abstract: PID tuning for chemical processes commonly relies on identified process models, whereas plant engineers often retune loops iteratively by observing re