Search: “models”

arXiv:2510.13903v2 Announce Type: replace-cross Abstract: Chain-of-thought prompting has popularized step-by-step reasoning in large language models, yet model performance still degrades as problem co

arXiv:2510.04876v3 Announce Type: replace Abstract: Benthic habitat mapping is fundamental for understanding marine ecosystems, guiding conservation efforts, and supporting sustainable resource manage

arXiv:2607.13234v1 Announce Type: cross Abstract: Deepfake detectors that achieve near-perfect scores on academic benchmarks collapse on real-world content: recent in-the-wild evaluations report AUC d

arXiv:2607.13038v1 Announce Type: cross Abstract: We present the design and implementation of a safety constrained large language model (LLM) system for public health information access, focusing on m

arXiv:2607.13792v1 Announce Type: new Abstract: Most daily activities are inherently procedural. However, existing evaluations for egocentric video understanding seldom address procedural understandin

arXiv:2607.13481v1 Announce Type: new Abstract: Accurate 3D scene understanding is fundamental to embodied intelligence and autonomous driving, where 3D occupancy provides a unified representation of

arXiv:2602.12811v2 Announce Type: replace-cross Abstract: When humans and large language models (LLMs) process the same text, activations in the LLMs correlate with brain activity measured, e.g., with

arXiv:2607.14086v1 Announce Type: new Abstract: Robust and accurate neural decoders are integral to neurotechnologies such as brain-computer interfaces and closed-loop experiments. Recent work has sho

arXiv:2607.13460v1 Announce Type: new Abstract: We present the Large Processing Model (LPM), a diffusion-based generative framework for photorealistic video restoration under complex, in-the-wild degr

arXiv:2607.13220v1 Announce Type: new Abstract: Most AI-for-science systems focus on scaling a single reasoning process through better models, larger context windows, long-horizon agentic execution, o

NVIDIAとSakana AI、オープンモデルによるイノベーションのため協業拡大 本日、Sakana AIはNVIDIAとのコラボレーションを強化し、日本発の「集合知」の取り組みを次なるフェーズへ進めることを発表します。 私たちのマルチエージェント・オーケストレーションシステム「Sakana Fugu」に、Nemotronファミリーを含むNVIDIAのオープンモデル群を統合します。 Sakana

arXiv:2607.13918v1 Announce Type: cross Abstract: Serial verification gates are a core reliability primitive in LLM harnesses: a candidate answer is returned only if k verifier calls all accept it. Un

arXiv:2607.13891v1 Announce Type: cross Abstract: Multi-object detection and tracking from noisy point clouds remain challenging in many data-scarce radar applications. Current Bayesian trackers based

arXiv:2607.13371v1 Announce Type: new Abstract: Accurate estimation of landfast sea ice roughness is critical for climate modeling and safe Arctic over-ice travel, yet existing approaches rely on cost

arXiv:2607.13081v1 Announce Type: cross Abstract: We present nsfaguard, a guardrail framework for securing agentic AI systems against operational threats, such as prompt injection, sensitive informati

arXiv:2607.13452v1 Announce Type: cross Abstract: Incremental object detection (IOD) aims to extend detectors to new categories while retaining previously acquired knowledge. Existing methods often ad

arXiv:2607.13988v1 Announce Type: new Abstract: Multi-turn agents solve complex tasks through extended sequences of tool interactions before producing a final answer, making credit assignment a fundam

arXiv:2607.10350v1 Announce Type: cross Abstract: Recent VLM and VLA systems have improved robotic perception and action prediction, yet long-horizon embodied agents still require a general runtime la

arXiv:2607.12122v1 Announce Type: new Abstract: We present an agentic approach to autonomous neural operator discovery based on an AI scientific community, which consists of a swarm of virtual laborat

arXiv:2607.12058v1 Announce Type: cross Abstract: Given a vulnerability-fixing commit, trigger localization asks which specific statement turns the vulnerable program state into a concrete unsafe oper

arXiv:2604.01506v2 Announce Type: replace Abstract: Long-tailed classification, where a small number of frequent classes dominate many rare ones, remains challenging because models systematically favo

arXiv:2601.08010v3 Announce Type: replace Abstract: Vision-language models achieve strong performance across a wide range of multimodal understanding and reasoning tasks, yet their multi-step reasonin

arXiv:2607.11958v1 Announce Type: new Abstract: Under the free energy principle, a predictive system does not observe reality directly; it maintains a generative model of the world and experiences tha

arXiv:2509.21842v2 Announce Type: replace Abstract: Travel planning (TP) agent has recently worked as an emerging building block to interact with external tools/resources for travel itinerary generati

arXiv:2508.05659v4 Announce Type: replace Abstract: Background: Causal loop diagrams (CLDs) are widely used in health and environmental research to represent hypothesized causal structures underlying

arXiv:2607.12462v1 Announce Type: new Abstract: Existing traffic forecasting models commonly focus on extracting spatial dependencies, particularly global spatial information, which characterizes the

arXiv:2607.12095v1 Announce Type: cross Abstract: Sensor-rich data-driven applications increasingly use Bayesian approaches to infer latent states of dynamic systems from noisy sensor measurements and

arXiv:2607.12065v1 Announce Type: cross Abstract: While visual navigation has been extensively studied in agricultural robotics, most existing systems assume daytime conditions. In fact, deploying aut

arXiv:2607.12931v1 Announce Type: new Abstract: Reinforcement Learning (RL) has demonstrated significant potential for improving Vision-Language-Action (VLA) models on complex manipulation tasks. Howe

arXiv:2607.12649v1 Announce Type: cross Abstract: Recent work on extractable memorization in LLMs suffers from two contrasting validity problems. Some studies overstate extraction, e.g., relying on se

arXiv:2505.16157v2 Announce Type: replace Abstract: Transformer-based models have made remarkable progress in image restoration (IR) tasks. However, the quadratic complexity of self-attention in Trans

arXiv:2607.12233v1 Announce Type: cross Abstract: Large language model (LLM) trading agents show promising performance in equity markets, yet remain narrowly focused on US equities with little evidenc

arXiv:2512.09925v2 Announce Type: replace Abstract: Recent advances in Gaussian Splatting-based inverse rendering extend Gaussian primitives with shading parameters and physically grounded light trans

arXiv:2603.16798v2 Announce Type: replace Abstract: We study mean estimation for a Gaussian distribution with identity covariance in R^d under a missing data scheme termed realizable epsilon-contamina

How I tricked Claude into leaking your deepest, darkest secrets I've been impressed by the way the Claude web_fetch tool is designed to avoid data exfiltration attacks. Ayush Paul found a hole in that

arXiv:2607.12450v1 Announce Type: new Abstract: This work introduces a unified formulation for vision models, where diverse forms of visual information beyond natural images, such as masks, depth maps

arXiv:2607.11916v1 Announce Type: cross Abstract: The integration of Large Language Models (LLMs) with evolutionary computation has emerged as a powerful paradigm for automated heuristic design in com

arXiv:2607.09759v2 Announce Type: replace-cross Abstract: Building assistants that can continually watch the world, remember what they see, and reason over their accumulated experience is a long-stand

arXiv:2607.11910v1 Announce Type: cross Abstract: Optimizing composite stacking sequences to match continuous targets (e.g., Lamination or Buckling Parameters) with discrete manufacturing constraints

🆕This Year In Claude https://www.youtube.com/watch?v=uU5Gv2h8-9g @simonw chats with @_catwu and @trq212 about the state of: - @claudeai Code - Claude Fable - @anthropicai culture & product strategy -

arXiv:2607.10467v2 Announce Type: replace-cross Abstract: Healthcare organizations often cannot freely centralize patient data because medical records are sensitive, regulated, and institutionally con

arXiv:2607.11933v1 Announce Type: new Abstract: Cross-encoders achieve high reranking accuracy in Retrieval-Augmented Generation (RAG) pipelines but impose quadratic inference costs that limit real-ti

arXiv:2607.12571v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models are deployed through pipelines that end users cannot audit, and a poisoned VLA can behave normally on clean observat

arXiv:2607.12800v1 Announce Type: new Abstract: Learning broad world knowledge directly from raw visual data is a fundamental capability of intelligence. We introduce UniVR, the first investigation in

arXiv:2607.12946v1 Announce Type: cross Abstract: Recommender-system research for Vietnamese remains limited by the absence of a public, well-documented hotel interaction resource. Building such a res

server : refactor prompt cache state ownership (#25649) server : clear checkpoints upon prompt clear server : move the prompt state data to the server_prompt_cache Assisted-by: pi:llama.cpp/Qwen3.6-27