Search: “models”

ToolLIFT: Lifting Tool-Specific Trajectories into Function-Level Graphs for Generalizable Tool Planning

arXiv:2608.03468v1 Announce Type: new Abstract: Historical tool-use trajectories provide valuable experience for large language model (LLM) agents to plan and coordinate tool usage. Existing approache

agentsarxiv-cs-ai

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Research

Topological Simplification in Predictive Coding Networks

DGX agent

arXiv:2608.02816v1 Announce Type: new Abstract: We study the topology of learned representations in predictive coding networks (PCNs), a neuro-inspired bidirectional architecture, using a quantitative

researcharxiv-cs-lg

5 Aug 2026

Towards Robust Tool Use in Agents via Experience-Driven Adaptive Guidance

arXiv:2608.03403v1 Announce Type: new Abstract: The performance bottleneck of agents is increasingly shifting from model capability to the robustness of their execution processes. Tools play a central

agentsarxiv-cs-ai

Unified Visuomotor Targets: Supervising VLAs Beyond Physical Actions

arXiv:2608.03563v1 Announce Type: new Abstract: VLA models are trained to predict robot actions from visual and language observations. This is a natural choice, but it creates a mismatch: VLMs encode

Applications

UNVaMP: Neural Knowledge Tracing with Variational Regularization of Latent Knowledge Dynamics

arXiv:2608.03811v1 Announce Type: new Abstract: We introduce the Unified Neural Variational Measurement of Proficiency (UNVaMP) architecture, a knowledge tracing method that integrates observed studen

applicationsarxiv-cs-lg

Variational Approximated Restricted Maximum Likelihood Estimation for Spatial Data

arXiv:2604.07635v2 Announce Type: replace-cross Abstract: This research considers a scalable inference for spatial data modeled through Gaussian intrinsic conditional autoregressive (ICAR) structures.

researcharxiv-cs-lg

What Language Does and What the Evidence Supports: A Functional Role Taxonomy and Evidence Audit of Language Grounding in Embodied Agents

arXiv:2608.03099v1 Announce Type: new Abstract: Foundation models place language throughout embodied agents, but its presence does not show what it contributes or how well that contribution is grounde

When and Where to Look: Adaptive Visual Evidence Scheduling for Efficient Long Video Understanding

arXiv:2608.03918v1 Announce Type: cross Abstract: Efficient long-video understanding requires vision--language models (VLMs) to reason over a small number of frames selected as sparse visual evidence.

local-aiarxiv-cs-ai

When Compression Scores Cannot Decide: Information Boundaries for Group-Robust LLM Pruning

arXiv:2608.02940v1 Announce Type: new Abstract: A reproducible compression statistic can still select the wrong candidate. A dense pruning score with 0.906 split-half reliability predicted a 16.1% gai

local-aiarxiv-cs-ai

When Oracle Conditioning Misleads Deployment: Conditioning-Availability Bias in Echocardiographic Segmentation

arXiv:2608.03342v1 Announce Type: cross Abstract: Conditional segmentation models may be trained and evaluated with auxiliary signals cleaner than those available at deployment. We study this protocol

safetyarxiv-cs-ai

When Teachers Mislead: Spurious-Signal-Aware On-Policy Distillation

arXiv:2608.03632v1 Announce Type: new Abstract: On-Policy distillation (OPD) transfers teacher capabilities by supervising student-sampled trajectories with dense token-level teacher signals. Recent s

safetyarxiv-cs-ai

3D-CovDiffusion: 3D-Aware Diffusion Policy for Coverage Path Planning

arXiv:2510.03011v2 Announce Type: replace Abstract: Diffusion models have shown strong potential for robot skill learning, yet their role in coverage path planning remains underexplored. In industrial

3DZip: Spatial-Aware Feature Diversity-Guided Token Compression for 3D Question Answering

arXiv:2608.01185v1 Announce Type: new Abstract: Recent 3D vision-language models (3D VLMs) construct geometry aware tokens by projecting 2D visual features into world coordinates, enabling spatial rea

Abstention as an Action Can Kill Both the Reward Gradient and the KL Anchor: Collapse Law and Repair for Error-Penalized Reinforcement Learning

arXiv:2608.00301v1 Announce Type: cross Abstract: Error-penalized scoring rules (+1 for a correct answer, -lambda for a wrong one, 0 for abstaining) are increasingly prescribed against hallucination:

agentsarxiv-cs-cl

Assessing the Impacts of Imperfect Datasets on Client Selections in Federated Learning

arXiv:2608.02250v1 Announce Type: new Abstract: Federated learning (FL) is a popular distributed learning framework where multiple clients perform local training and a server aggregates the locally up

local-aiarxiv-cs-lg

Attend to Your Own Thoughts: Breaking the Barrier for Post-Training Quantization of Reasoning LLMs through the Lens of 1.58-Bit Quantization

arXiv:2608.01078v1 Announce Type: new Abstract: We propose ScaleQ-1.58, a scalable ternary post-training quantization (PTQ) framework for reasoning LLMs. Its core insight stems from an empirical findi

Benign Overfitting in Linear Classifiers with a Bias Term

arXiv:2511.12840v2 Announce Type: replace-cross Abstract: Overparameterized models often generalize well even when they interpolate noisy training data. This is known as benign overfitting. For linear

Breaking the Statistical Similarity Trap in Extreme Convection Detection

arXiv:2509.09195v2 Announce Type: replace-cross Abstract: Current evaluation metrics for deep learning weather models create a 'Statistical Similarity Trap', rewarding blurry predictions while missing

safetyarxiv-cs-cv

Can AI Agents Simulate A/B Test Outcomes? A Validation Framework for Agentic Experimentation

arXiv:2608.02345v1 Announce Type: new Abstract: A/B testing remains the standard for rolling out new features in the technology industry. Each experiment, however, consumes real traffic, engineering e

agentsarxiv-cs-cl

CascadeLUT: Information-Ordered Streaming Inference for Bandwidth-Constrained FPGAs

arXiv:2608.00720v1 Announce Type: cross Abstract: Mapping neural networks to FPGAs enables low-latency, energy-efficient inference, particularly for lookup table (LUT)-based models that eliminate mult

local-aiarxiv-cs-lg

Tutorials

Coverage-Driven Adaptive Keyframe Selection for Video Understanding

arXiv:2608.00714v1 Announce Type: new Abstract: Recent advances in large vision-language models (LVLMs) have enabled long-video understanding and analysis. However, processing the large number of fram

tutorialsarxiv-cs-cv

CoWAM: Coordination Contracts for Selective Policy Intervention with WAMs

arXiv:2608.02578v1 Announce Type: cross Abstract: World Action Models (WAMs) augment robot policies with action-conditioned predicted futures, but a plausible future alone does not justify changing th

Credit the Right Box: Marginal Contribution Assignment for Structured Visual Perception

arXiv:2608.01055v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) are increasingly expected to solve structured perception tasks that require visual recognition, language-to-obj

Cultural Awareness is Represented but Not Decoded: Tracing Mythological Knowledge across 18 Open-Source LLMs

arXiv:2608.02486v1 Announce Type: new Abstract: Open-source LLMs reliably name Zeus, Jupiter, and Thor, but recover their counterparts in less-represented traditions like Finnish, Slavic, Egyptian, or

D^2-4DGS: Dual-Depth Guided Sparse-Camera 4D Gaussian Splatting

arXiv:2608.01588v1 Announce Type: new Abstract: Dynamic 4D Gaussian Splatting has emerged as an efficient representation for dynamic novel view synthesis through explicit scene modeling and real-time

Decisions over Sequences: Computability and Choice

arXiv:2203.00070v3 Announce Type: replace-cross Abstract: We develop a framework to study situations where decision makers face alternatives sequentially. Within this framework, we focus on endogenous

Deep Research Pretraining via Predictive Navigation

arXiv:2608.00432v1 Announce Type: new Abstract: Deep research agents are often trained on expensive, environment-grounded tool-use trajectories that require repeated retrieval, document inspection, an

safetyarxiv-cs-cl

DeepDefense: Robust Learning via Layer-Wise Gradient-Feature Alignment

arXiv:2511.13749v2 Announce Type: replace Abstract: Deep neural networks are known to be vulnerable to adversarial perturbations, which are small, carefully crafted inputs that lead to incorrect predi

Demystifying When and Why VLAs Fail in Contact-Rich Tasks and How to Fix Them

arXiv:2608.01402v1 Announce Type: new Abstract: We address the problem of understanding when and why Vision-Language-Action models struggle with contact-rich manipulation tasks that require precise ph

Detecting Nonproperness of Likelihood Equations

arXiv:2608.01976v1 Announce Type: cross Abstract: Given an algebraic statistical model, a challenging problem is classifying the data according to the number of positive critical points of the likelih

researcharxiv-cs-lg

DiffuseAgent-MI: Distributionally-Grounded,Tool-Integrated Self-Evolving Agents for Faithful Visual Reasoning

arXiv:2608.00540v1 Announce Type: new Abstract: Tool-integrated vision-language agents have made remarkable progress on compositional and multi-step visual reasoning. Yet their outputs frequently exhi

safetyarxiv-cs-cv

Tutorials

Diffusion-Based Body Schema Learning Enabling Abnormal-State Adaptation in Musculoskeletal Robots

arXiv:2608.01029v1 Announce Type: new Abstract: Musculoskeletal robots require an internal body schema that remains consistent under a wide range of physical state changes, including abnormalities suc

tutorialsarxiv-cs-ro

Disentangled Contrastive Learning for Zero-Shot Multilingual Dense Retrieval

arXiv:2608.02189v1 Announce Type: cross Abstract: Multilingual dense retrieval aims to handle queries and documents across different languages based on a unified retriever model. The challenge lies in

safetyarxiv-cs-cl

Distributional Matching for Vector Quantization: A Unified Theoretical and Empirical Framework

arXiv:2607.15933v2 Announce Type: replace Abstract: The effectiveness of modern visual representation learning and autoregressive models critically depends on vector quantization (VQ), which discretiz

Applications

Does the Competitive Component of Adversarial Self-Play Improve Legal Reasoning? A Controlled Negative Result

arXiv:2608.01559v1 Announce Type: cross Abstract: Adversarial self-play is an appealing recipe for legal reasoning: have a student model draft an argument, have an adversary attack it, and reward the

applicationsarxiv-cs-cl

DreamTraj: Generating 6-DoF Object Trajectories by Reading Unrendered Video Diffusion Latents

arXiv:2608.00486v1 Announce Type: new Abstract: Accurate prediction of object trajectories during manipulation is essential for closing the perception-action loop. Progress is limited on two fronts: a

Dynamic Resolution Routing for Efficient Egocentric Grounding

arXiv:2608.01638v1 Announce Type: new Abstract: Egocentric visual grounding requires high-resolution inputs to localize small objects. However, scaling Multimodal Large Language Models to this domain

local-aiarxiv-cs-cv

Exploiting Intrinsic Duality for Multi-Hop Question Generation

arXiv:2608.00712v1 Announce Type: new Abstract: Multi hop question generation (MQG) aims to generate questions from multiple given documents and target answers, whereas question answering (QA) focuses

safetyarxiv-cs-cl

FactorJEPA: Factorizing Monolithic Futures into Layout-Agent-Interaction Channels for Crowded and Chaotic Global South Urban Worlds

arXiv:2608.01049v1 Announce Type: cross Abstract: World models have attracted significant attention for their ability to capture and predict the structure and dynamics of the physical world. In this e

agentsarxiv-cs-cv

FAST-GS: Frequency Aware Space-time Gaussian Splatting for Photorealistic Dynamic Novel View Synthesis

arXiv:2608.01958v1 Announce Type: new Abstract: 4D Gaussian Splatting (4DGS) excels in dynamic 3D reconstruction and real-time novel view synthesis via efficient 4D Gaussian representations and parall

local-aiarxiv-cs-cv

FAU at ImageCLEF 2026 Task on Multimodal Reasoning Robust Candidate Scoring and Concise Multilingual Visual Answering

arXiv:2608.01664v1 Announce Type: new Abstract: We present our ImageCLEF 2026 Multimodal Reasoning system for the Visual Multiple Choice Question Answering (Visual MCQ) and Visual Open Question Answer

From Chains to Trees: Parent-Conditioned Drafting for Semi-Autoregressive Speculative Decoding

arXiv:2608.02123v1 Announce Type: new Abstract: Speculative decoding accelerates LLM inference only when drafted continuations survive target-model verification. Semi-autoregressive drafters such as D

From fragmented data to actionable design: Physics-calibrated learning for plastic upcycling

arXiv:2608.02402v1 Announce Type: new Abstract: Thermochemical upgrading of plastic waste is a key upcycling pathway, yet the experimental literature is fragmented by heterogeneous conditions and inco

researcharxiv-cs-lg

From Pixels to PCells: A Neurosymbolic Approach to Photonic Component Creation

arXiv:2608.00084v1 Announce Type: new Abstract: We present PixCell, a neurosymbolic system in which multimodal agents convert a visually presented photonic component into a parametric program over a s

GAPSL: A Gradient-Aligned Parallel Split Learning over Data-Heterogeneous Edge Computing Systems

arXiv:2603.18540v2 Announce Type: replace Abstract: The increasing complexity of neural networks poses significant challenges for democratizing federated learning (FL) on resource-constrained edge dev

Tutorials

Generative Brownian Bridge Diffusion In Motion Space For Enhanced Myocardial Strain Analysis

arXiv:2608.01677v1 Announce Type: new Abstract: Myocardial strain analysis of cardiac magnetic resonance (CMR) images provides an important tool for evaluating cardiac function. However, current techn

tutorialsarxiv-cs-cv

Gimbal360: Canonicalizing Planar Diffusion for Spherical Panorama Completion

arXiv:2603.23179v2 Announce Type: replace Abstract: Diffusion models provide powerful priors for 2D image completion, but these priors are learned on bounded planar images and do not transfer directly

Grounded Vision-Language Interpreter for Long-Horizon Bimanual Task and Motion Planning

arXiv:2506.03270v3 Announce Type: replace Abstract: While recent advances in vision-language models have accelerated language-guided robot planning, their black-box nature lacks the safety guarantees