Search: “evaluation”

Falsehood and Impossibility Are Different Directions in an AI's Representation of Language

arXiv:2608.12852v1 Announce Type: cross Abstract: Language can describe states of affairs that are false and states of affairs that could not be the case at all. Whether an AI model internally disting

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Research

Fast Iterative Five point Relative Pose Estimation

DGX agent

arXiv:2608.13114v1 Announce Type: new Abstract: Robust estimation of the relative pose between two cameras is a fundamental part of Structure and Motion methods. For calibrated cameras, the five point

researcharxiv-cs-cv

14 Aug 2026

Fine-tuned Normalizing Flows for ALICE Zero Degree Calorimeter Fast Simulation

arXiv:2608.12795v1 Announce Type: cross Abstract: Simulating the ALICE Zero Degree Calorimeter (ZDC) neutron detector responses at the LHC is computationally expensive, requiring complex Monte Carlo c

researcharxiv-cs-lg

Finite-Time Minimax Bounds and an Optimal Lyapunov Policy in Queueing Control

arXiv:2506.18278v4 Announce Type: replace-cross Abstract: We introduce an original minimax framework for finite-time performance analysis in queueing control and propose a surprisingly simple Lyapunov

safetyarxiv-cs-lg

Fixed/improved Jinja chat template for Qwen 3.8

model-releasesr-localllama

'Again?' you might ask. I(*) took the original Qwen 27B 3.8 chat template and compared it to the improved template that was posted a day before. The original has issues. The improved one fixed some wh

Follow the Norm: Accounting for Fine-Tuning and Prompt Effects on Model Rationales

arXiv:2608.13250v1 Announce Type: cross Abstract: Normative datasets are often used to train and align AI systems, but the norms they contain can function as action-guiding patterns rather than neutra

Foundation models for movement data: Are they ready for prime-time?

arXiv:2608.13316v1 Announce Type: cross Abstract: Foundation models (FMs) trained on large-scale accelerometer data have been proposed as general-purpose feature extractors for health monitoring, but

researcharxiv-cs-lg

Foundations of MT-PDCL: Measure-Theoretic Probabilistic Definite Clause Logic

arXiv:2608.13018v1 Announce Type: new Abstract: Standard probabilistic logic programming frameworks typically rely on grounding logic programs into discrete propositional representations. This operati

From Atomic Evidence to Logical Composition: Structured Compositional Reasoning over Compound Answer Options

arXiv:2608.12836v1 Announce Type: cross Abstract: Large language models often fail when answer options require combining atomic judgments under explicit logical operators, even when they judge the ind

From Refuse to Richness: Rubric Rewards for Long-Form Hallucination Reinforcement Learning

arXiv:2608.12337v1 Announce Type: new Abstract: Rewards that penalize unsupported claims can improve grounding in long-form generation, but they can also teach models to answer less. We study this ref

From Visual Widgets to UI Code: Efficient Tool-Grounded Generation

model-releasesarxiv-cs-cv

arXiv:2608.12611v1 Announce Type: new Abstract: Existing screenshot-to-code systems face a trade-off between flexibility and controllability. Direct multimodal generation can hallucinate visible detai

FUSE: Active Functional Affordance Grounding through Adaptive Semantic-Geometric Evidence Acquisition

model-releasesarxiv-cs-cv

arXiv:2608.12683v1 Announce Type: cross Abstract: Embodied agents must often identify and interact with objects based on their function rather than their identity, requiring them to actively acquire o

GEM: A Generative Embedding Model Bridging Reasoning and Retrieval

arXiv:2608.13200v1 Announce Type: cross Abstract: Modern LLMs excel at reasoning and instruction following, enabling users to express complex and diverse information needs. However, conventional retri

Generative Universal Multimodal Retrieval with Dual-role Identifiers

arXiv:2608.12987v1 Announce Type: cross Abstract: Generative information retrieval (GIR) has emerged as a compelling alternative to the conventional index-retrieve-then-rank retrieval pipeline by trai

History-informed Lagrangian Neural Networks

model-releasesarxiv-cs-lg

arXiv:2608.13215v1 Announce Type: new Abstract: Forecasting the long-horizon evolution of mechanical systems from position-only observations is a pivotal yet difficult task, as hidden velocities and t

InFactPlanner: Planning Sustainable Geo-Distributed LLM Data Centers

arXiv:2608.12915v1 Announce Type: cross Abstract: The rapid growth of LLM inference is shifting sustainability concerns from one-time training to continuous serving, where infrastructure decisions sha

Intensional Anaphora

arXiv:2608.12598v1 Announce Type: new Abstract: Intensional operators are often treated as quantifiers over possible worlds, parallel to the treatment of determiners as quantifiers over individuals. Y

Intern-S2-Preview: Scientific Agentic Foundation Model

arXiv:2608.13505v1 Announce Type: cross Abstract: Scientific discovery increasingly requires AI systems that can reason over scientific evidence of heterogeneous modalities, interact with scientific t

safetyarxiv-cs-cl

Into the ORBIT for Time Series: Training Regimes for Foundation Models

arXiv:2608.13262v1 Announce Type: cross Abstract: Time series foundation models (TSFMs) have advanced primarily through architectural innovation, while training regimes for large-scale heterogeneous c

safetyarxiv-cs-ai

Large Language Models Can Follow Instructions, But Not Many at Once: Phase Transitions in Compositional Constraint Satisfaction

arXiv:2608.12426v1 Announce Type: new Abstract: Large language models are increasingly deployed in settings that require simultaneous adherence to multiple explicit constraints - reasoning structure,

Learning Discrete Decisions for MIPs with Constraint-Aware Diffusion

arXiv:2608.13079v1 Announce Type: new Abstract: This paper proposes a novel learning-based approach to approximately solve instances of mixed-integer optimization problems. These problems are computat

researcharxiv-cs-lg

Learning Latency-Aware Orchestration for Multi-Agent Systems

arXiv:2601.10560v2 Announce Type: replace-cross Abstract: Multi-agent systems (MAS) coordinate multiple LLM-powered agents through structured workflows, gaining reasoning power but incurring high infe

agentsarxiv-cs-ai

Less Annotation, More Interpretation: Prior-Guided Concept Bottleneck Models for Interpretable Cancer Imaging Diagnosis

arXiv:2608.13148v1 Announce Type: new Abstract: Concept bottleneck models (CBMs) can improve the transparency of cancer image diagnostic prediction by expressing predictions through radiological conce

researcharxiv-cs-cv

LittleLearner: Language Models Under Pedagogically Controlled Knowledge Exposure

arXiv:2608.13545v1 Announce Type: cross Abstract: Modern language models are trained on heterogeneous web-scale text corpora. Consequently, studying knowledge and skill acquisition is difficult, as pr

Local Ai

LLM-Guided Graph Generation for Structure-Based Local Improvement Methods

arXiv:2608.13333v1 Announce Type: new Abstract: Large neighborhood search normally selects a random subset of decision variables for iterative optimization. For efficiently solving different problems,

local-aiarxiv-cs-ai

Local Ai

LLMs Are Not Good Strategists, Yet Memory-Enhanced Agency Boosts Reasoning

arXiv:2608.12626v1 Announce Type: cross Abstract: Strategic reasoning in Large Language Models (LLMs) within long-horizon environments is often limited by inconsistent subgoals. In these settings, fin

local-aiarxiv-cs-ai

LoRA-Diffusion: Parameter-Efficient Fine-Tuning via Low-Rank Trajectory Decomposition

model-releasesarxiv-cs-cl

arXiv:2608.12328v1 Announce Type: new Abstract: Parameter-efficient fine-tuning methods such as LoRA have transformed the adaptation of large autoregressive language models, enabling task-specific cus

MapRoute++: Surrogate-Guided Semantic Routing for Visual Concept Unlearning

model-releasesarxiv-cs-cv

arXiv:2608.13478v1 Announce Type: new Abstract: We present our submission to Task 3 of the Genmu 2.0 Challenge on visual concept unlearning. Building on MapRoute, we introduce task-specific training o

Local Ai

MARC v1: An Open-Source Multi-Agent Framework for Clinical AI Reasoning and Coordination

arXiv:2608.13476v1 Announce Type: new Abstract: We present Multi-Agent Reasoning and Coordination (MARC), an open-source framework that replaces monolithic LLM prompting with deterministic multi-agent

local-aiarxiv-cs-ai

Mind the Context: Continual Learning of Socially Appropriate Robot Actions via Environmental-Social Disentanglement

arXiv:2608.13448v1 Announce Type: new Abstract: Social robots are expected to operate across diverse environments, where similar arrangements can imply different socially appropriate actions, e.g., st

agentsarxiv-cs-ro

MindMemOS: A Portable and Self-Evolving Memory Operating Layer for AI Agents

arXiv:2608.12428v1 Announce Type: new Abstract: Memory is a core component of AI agents, enabling them to accumulate experience, maintain personalization, and adapt over long-term interactions. Howeve

agentsarxiv-cs-ai

MLLM-Routed Heterogeneous Ensembles for Robust Cross-Dataset Image Classification

arXiv:2608.13463v1 Announce Type: cross Abstract: Modern image classification models excel when trained on single task-specific datasets but often struggle to generalize across domains and difficulty

agentsarxiv-cs-ai

Applications

Moose: Latent concept learning with reasoning-shortcut awareness in EL^{++}

arXiv:2608.12961v1 Announce Type: new Abstract: The OWL 2 EL profile is used in some of the largest production ontologies, including the Gene Ontology and SNOMED CT. Existing neuro-symbolic (NeSy) lea

applicationsarxiv-cs-ai

Motor, Cognitive, or Corpus? What Survives Cross-Lingual Transfer in Speech-Based Parkinsons Disease Detection

arXiv:2608.13425v1 Announce Type: new Abstract: Self-supervised learning (SSL) speech representations achieve strong performance for Parkinson's disease (PD) detection within individual corpora. Howev

Mr3D-VL: A generalist vision language foundation model for Multiparametric 3D Magnetic Resonance Imaging

arXiv:2608.12689v1 Announce Type: cross Abstract: Multi-parametric magnetic resonance imaging (mpMRI) is a cornerstone for brain tumor diagnosis and treatment, yet current AI models face critical limi

safetyarxiv-cs-ai

Multi-Layer Context Camouflaging: A Semantic Superposition and Contextual Lamination Framework for Malpractice-Resilient Online Assessment

arXiv:2608.13100v1 Announce Type: new Abstract: Contemporary online assessment systems rely primarily on browser lockdown, webcam monitoring, and behavioural analytics, yet remain vulnerable to attack

NestDex: Nested Policy Learning with Copilot Assisted Teleoperation for Dexterous Manipulation

arXiv:2608.13362v1 Announce Type: new Abstract: Dexterous manipulation promises substantially richer robot interaction with the physical world, but learning these behaviours remains constrained by the

safetyarxiv-cs-ro

Applications

Optimizing Likelihoods via Mutual Information: Bridging Simulation-Based Inference and Bayesian Optimal Experimental Design

arXiv:2502.08004v2 Announce Type: replace-cross Abstract: Simulation-based inference (SBI) is a method to perform inference on a variety of complex scientific models with challenging inference (invers

applicationsarxiv-cs-lg

P2Fusion: Prompt-based Progressive Infrared-Visible Image Fusion via Dual-Prior Distillation

arXiv:2608.13045v1 Announce Type: new Abstract: Infrared-visible image fusion (IVIF) is pivotal for multimodal perception, yet reconciling the inherent information disparity between thermal and textur

researcharxiv-cs-cv

Pandora: Leveraging Code-driven Knowledge Transfer for Unified Structured Knowledge Reasoning

arXiv:2508.17905v2 Announce Type: replace Abstract: Unified Structured Knowledge Reasoning (USKR) aims to answer natural language questions by using structured sources such as tables, databases, and k

PatchGen: Learning Soft Intra-Image Predictive Subsets for Visual Generalization

arXiv:2608.12766v1 Announce Type: new Abstract: Visual classifiers are expected to generalize under data shifts, target shifts, and their combinations, yet most existing methods focus on domain invari

researcharxiv-cs-cv

Perception-Aware Autonomous Exploration in Feature-Limited Environments

arXiv:2603.15605v2 Announce Type: replace Abstract: Autonomous exploration in unknown environments typically relies on onboard state estimation for localisation and mapping. Existing exploration metho

agentsarxiv-cs-ro

PIPES: Securing Agent Perception with Provenance and Priors

arXiv:2608.12789v1 Announce Type: cross Abstract: Tool-using agents consume external data from sources with different levels of trust, yet tool responses rarely identify who produced each component or

Predicting consumer-technology ownership without a diffusion history

model-releasesarxiv-cs-cl

arXiv:2608.12344v1 Announce Type: new Abstract: We test whether the perceived attributes of a consumer technology predict how widely it is owned. In a 2022 Prolific survey of US adults (n = 678), resp

Predictive Allostatic Organization in Recurrent and Spiking Agents Under Partial Observability

model-releasesarxiv-cs-lg

arXiv:2608.11506v1 Announce Type: cross Abstract: Adaptive behavior under partial observability depends on internal organization that carries information beyond the current observation. Drawing on Bar

ProME: Prototype-Margin Environments with Repair-Aware Selection for Group-Robust Learning

arXiv:2608.13190v1 Announce Type: cross Abstract: Group-robust learning is crucial for maintaining accuracy on rare subpopulations when training-group labels are unavailable. However, existing methods

safetyarxiv-cs-cv

PROVE-RT: Generating Mechanized Theorem Prover Scripts for Real-Time Systems using LLMs

arXiv:2608.12762v1 Announce Type: new Abstract: Schedulability analysis is essential for certifying real-time systems, but existing tests are often developed through pen-and-paper proofs that are diff

Query Timing Produces Opposite Positional Biases Between LLMs and Humans

arXiv:2608.12387v1 Announce Type: cross Abstract: Positional biases such as recency and primacy effects have been documented in large language models (LLMs), yet the underlying mechanism by which thes