Search: “agents”

arXiv:2609.22910v1 Announce Type: new Abstract: Vision-language agents that crop and zoom are trained with rewards that credit a successful tool call, yet a successful call does not show that the mode

arXiv:2609.22249v1 Announce Type: new Abstract: This paper treats prompt engineering as a discipline for turning informal human intent into structured AI work specifications. It develops the practice

At Box, we've been testing Opus 5.5 on a variety of complex enterprise knowledge work tasks dealing with unstructured data with the Box Agent. Overall, we saw frontier capability levels, with major pe

arXiv:2609.22248v1 Announce Type: new Abstract: Systematic Literature Reviews (SLRs) are essential for evidence-based research but remain time-consuming, requiring researchers to manage large volumes

Claude Opus 5.5, Anthropic's most capable Opus model for agentic coding, knowledge work, and long-running tasks, is now available on Amazon Bedrock and Claude Platform on AWS. This post covers what's

arXiv:2609.24208v1 Announce Type: new Abstract: We ask how little geometry a person has to draw to control both where people stand and where the camera moves in a generated video. Our answer is a grou

arXiv:2609.23043v1 Announce Type: cross Abstract: Large Language Models (LLMs) enable open-ended dialogue in interactive games, but their non-deterministic outputs make it difficult to preserve author

arXiv:2609.22231v1 Announce Type: new Abstract: Long-horizon interactions with LLM-based assistants require memory systems that preserve and update user states, preferences, and interaction histories.

arXiv:2609.22611v1 Announce Type: new Abstract: Humanoid robots can acquire complex skills by imitating kinematic humanoid motion references, yet reliable references for contact-rich interactions rema

Some people here say MiMo-V2.6 is bad with tools and are going back to GLM-5.3-Flash. I spent today running MiMo-V2.6-Flash-RL as the backend for an agent harness, on 2× DGX Spark with vLLM, using the

• Ming-Image-0.1-Design, 6B • Ming-Image-0.1-Design-Layer, 6B • Two open-source Agent Skills: the Ling UI Design Skill and the Image-to-Editable-PPT Skill Ming-Image-0.1-Design ranks #1 among open-wei

arXiv:2609.24703v1 Announce Type: cross Abstract: Data-driven protection may complement conventional relays in distribution grids whose operating conditions vary with distributed generation, switching

arXiv:2511.07260v3 Announce Type: replace-cross Abstract: Ad hoc teamwork (AHT) requires agents to collaborate with previously unseen teammates, which is crucial for many real-world applications. The

arXiv:2609.22325v1 Announce Type: new Abstract: Large language models have shown considerable potential for natural-language-driven parametric CAD modeling. However, a fundamental contradiction exists

arXiv:2609.22966v1 Announce Type: new Abstract: Humans can seamlessly adapt to both physical and digital worlds, suggesting that while a digital-to-real gap exists in embodiment, environment and task,

Todd Bishop / GeekWire: Amazon says it blocked Meta's Muse AI assistant from accessing Amazon.com to shop on users' behalf, citing ToS violations, security risks, and merchant consent — Amazon says it

Document classification and splitting idea using @typesafeai Jev based on LiteParse, and LlamaParse. Classify: categorize probabilities, and review flags. Measure: separate OCR and decision timing, pr

arXiv:2609.20827v1 Announce Type: new Abstract: Hospital discharge education is an interactive teaching task: a clinician adapts a discharge plan to a patient's literacy, recall, and personality. Exis

arXiv:2602.07036v2 Announce Type: replace-cross Abstract: Audio large language models (AudioLLMs) enable instruction following over speech and general audio, but progress is limited by the scarcity of

arXiv:2609.21554v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have revolutionized artificial intelligence and how human interact with AIs. Despite impressive advancem

Morgan Stanley's Adam Jonas in new note: 'SpaceX and Tesla share tech, talent, and infrastructure in a shared mission of converting energy to intelligence. In our view, it is the belief of Elon Musk &

arXiv:2609.21967v1 Announce Type: cross Abstract: We introduce NemotronLabs VoiceChat, an open full-duplex speech-to-speech model with native tool-calling capabilities. NemotronLabs VoiceChat combines

arXiv:2609.20880v1 Announce Type: cross Abstract: Direct imaging of exoplanets is limited by the extreme contrast between the star and the planets, which is mitigated using a coronagraph. However, opt

arXiv:2209.05333v2 Announce Type: replace Abstract: Learning task-relevant representations is crucial for reinforcement learning. Recent approaches aim to learn such representations by improving the t

5x faster than LLMs while being 13% cheaper than GPT 5.6 Luna, 88% cheaper than GPT 5.6 terra and 99% cheaper than Sonnet 4.6 is insane Has anyone else used Jev for evals? We tested Jev against LLM ju

i have been running local models as browser agents on an m5 macbook pro, 128gb, all through mlx, no cloud. first i just wanted to know which one was faster at real browser work, so i gave gemma 4 31b

'jev as a judge' cheap and fast semantic verifiers! great for evals - especially online evals where you want to grade LOTS of traces We tested Jev against LLM judges on accuracy, repeatability, latenc

TL;DR: Local agent loop, ~21 days, one RTX 3090. Task was pretty much 'build a CUDA inference engine for optimized for yourself on this GPU arch.' Got working kernels and benches, not a win over llama

Josipa Majic Predin / Forbes: Vercel, Cloudflare, and others quickly add Jev, as it makes AI tool selection much faster and cheaper; TypeSafe: Jev matches GPT-5.6 and Sonnet 5 workflow evals — Most of

A great example of practical AI solving real-world problems! Faster than ever. Thanks for building with Qwen. @cerebras Try it out for yourself! 🏠 We built Money Agent, a personal finance assistant po

One of the craziest use cases I’ve found for Jev: verifiers. I am so excited about this that I at least wanted to share the high-level idea. I used Jev to build a custom verifier for the /goal feature

arXiv:2609.20722v1 Announce Type: new Abstract: Activation steering modifies LLM behavior at inference time, but identifying where and how strongly to steer remains manual. We introduce Deep Noir, a f

arXiv:2609.19969v1 Announce Type: new Abstract: The widespread adoption of long-horizon agents has made model workloads increasingly input-heavy. Although prior work has substantially reduced the cost

arXiv:2609.20116v1 Announce Type: new Abstract: We study GPT-6-Astra in a zero-shot Vision-and-Language Navigation in Continuous Environments (VLN-CE) system, where it interprets instructions, assesse

arXiv:2609.19814v1 Announce Type: cross Abstract: Landmark mathematical formalizations have taken specialist teams years to complete. We present FormalFlow, a system that coordinates AI proving agents

arXiv:2511.15227v2 Announce Type: replace Abstract: Model-based development accelerates prototyping, enables earlier experimentation, and ensures rigorous validation of system design intents. In multi

arXiv:2609.20319v1 Announce Type: cross Abstract: Grover search, amplitude amplification, and quantum counting all rely on the same reusable subroutine, a phase oracle, whose construction the algorith

The simple truth: not even Anthropic has a plan for how to make AI safe in advance. There is no theory. I've asked! Outside evaluators don't change the situation. No one at these companies has workabl

arXiv:2609.19662v1 Announce Type: new Abstract: Cross-view object geo-localization (CVOGL) typically assumes a fixed query image, overlooking the ability of mobile agents to actively acquire more info

arXiv:2609.19813v1 Announce Type: new Abstract: Predicting the future trajectories of surrounding vehicles in autonomous driving is important for collision risk assessment and safe ego-vehicle path pl

arXiv:2609.20480v1 Announce Type: new Abstract: Occlusion creates fundamental uncertainty in autonomous driving. Existing methods often propagate frame-wise hypotheses or optimize ego behavior against

arXiv:2609.18881v1 Announce Type: new Abstract: First-person-view (FPV) teleoperation of aerial swarms requires an operator to coordinate collective translation, viewing direction, and formation spaci

arXiv:2609.18620v1 Announce Type: new Abstract: Creating deformable assets for robot manipulation requires jointly specifying their geometry, appearance, and physical properties. This is especially ch

arXiv:2609.18238v1 Announce Type: new Abstract: Observational decision-support systems often expose one causal estimate as a recommendation even when plausible estimators disagree. The inherent engine

arXiv:2609.17856v1 Announce Type: cross Abstract: Heterogeneous cooperative perception (CP) enables connected vehicles with diverse sensor setups to share spatial awareness via compact feature maps, w

arXiv:2609.18511v1 Announce Type: cross Abstract: In autonomous driving, perception models often struggle to generalize to new environments due to domain shifts. While unsupervised model adaptation of