Search: “reasoning”

Approximation of solutions of parameter-dependent problems by residual neural networks

model-releasesarxiv-cs-lg

arXiv:2607.13574v1 Announce Type: cross Abstract: We develop a convergent scheme to train neural networks involving analytic activation functions based on gradient flows. Convergence properties are gu

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Agents

Automatic Ordinary Differential Equations Discovery For Biological Systems Using Large Language Model Powered Agentic System

DGX agent

arXiv:2607.13608v1 Announce Type: new Abstract: Automatic scientific discovery has long been a goal of computational scholars - a machine that can discover nature's secrets on its own, moving computat

agentsarxiv-cs-ai

16 Jul 2026

Concurrent Image Understanding and Generation: Self-Correcting Coupled Markov Jump Processes

arXiv:2607.13188v1 Announce Type: new Abstract: Human cognition does not separate understanding and generation. A teacher at a whiteboard speaks and draws extit{together}, each modality reshapes the o

researcharxiv-cs-lg

Cost-Optimal Foundation Model Deployment Portfolio for Transportation Management

arXiv:2607.13239v1 Announce Type: new Abstract: Foundation models, including large language models (LLMs) and vision-language models (VLMs), are increasingly used for transportation management center

Exploratory, Communicative, and Deployable: Vision-Driven Embodied Agents for Open-World Mobile Manipulation

arXiv:2607.13653v1 Announce Type: new Abstract: Real-world deployment of embodied agents requires active exploration, visual grounding, and interactive intent disambiguation. However, existing framewo

GPOcc++: Unified Sparse Gaussian Occupancy Prediction with Visual Geometry Priors

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

Grounded world models in biological organisms and future embodied AI

arXiv:2607.13560v1 Announce Type: cross Abstract: Recent advances in generative and embodied AI have been driven by large-scale predictive learning over multimodal data. However, the resulting systems

agentsarxiv-cs-ai

Human4K: A Large-Scale 4K Multi-View Mocap Dataset for Whole-Body 3D Human Reconstruction

arXiv:2607.13646v1 Announce Type: cross Abstract: Recent advances in 3D human reconstruction have improved overall performance, yet current models still fail in the most challenging real-world scenari

Improving Molecular Property Prediction in Small Language Models Using Graph-based Tools

arXiv:2607.13115v1 Announce Type: new Abstract: Small language models (SLMs) have shown promise for zero-shot molecular property prediction from SMILES strings, yet they often suffer from structural b

agentsarxiv-cs-ai

Interaction Protocol Shapes Moral Judgment in Multi-Agent Debate

arXiv:2510.10002v3 Announce Type: replace Abstract: As large language models (LLMs) are increasingly deployed in sensitive everyday contexts -- offering personal advice, mental health support, and mor

Joint On-and-Off Policy Learning for Vision-and-Language Navigation

arXiv:2607.13461v1 Announce Type: new Abstract: Vision-and-Language Navigation (VLN) necessitates an embodied agent to navigate in the physical world by adhering to natural language instructions. Rece

safetyarxiv-cs-ro

Learning Red Agent Policy from Observations for Neurosymbolic Autonomous Cyber Agents

arXiv:2606.18223v2 Announce Type: replace-cross Abstract: With sophisticated cyber-attacks becoming increasingly prevalent, modern networks require intelligent autonomous cyber-defense agents trained

Learning Robust Execution in Robotic Manipulation with Agentic Reinforcement Learning

model-releasesarxiv-cs-ro

arXiv:2607.13818v1 Announce Type: new Abstract: Robotic manipulation poses fundamental challenges due to uncertainty, long-horizon execution, and compounding errors, which can easily destabilize execu

Learning Safe Agent Behaviour from Human Preferences and Justifications via World Models

arXiv:2607.13172v1 Announce Type: new Abstract: We address the problem of safely training an agent policy and deploying a good and safe policy, in settings where the environment dynamics are unknown a

Left-right asymmetry in predicting brain activity from LLMs' representations emerges with their formal linguistic competence

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

MedRealMM: A Real-World Multimodal Benchmark for Chinese Online Medical Consultation

arXiv:2607.09142v2 Announce Type: replace Abstract: Large language models (LLMs) are increasingly deployed in online medical consultation, yet existing benchmarks remain poorly aligned with real clini

Quantum Circuit Vision: Cost-Aware Evaluation of Visual AI Agents for Quantum Code Generation

arXiv:2607.10057v1 Announce Type: cross Abstract: Can AI agents visually comprehend quantum circuit diagrams and generate verified executable code--and at what cost? We present Quantum Circuit Vision,

Tutorials

Reflecting Process Expertise in Procedural Material Generation

arXiv:2607.13318v1 Announce Type: new Abstract: Procedural material creation underpins applications in digital content creation, visual effects, and 3D asset design. Achieving high-quality results req

tutorialsarxiv-cs-cv

ShortOPD: Recovering Pruned LLMs with Short-to-Long On-Policy Distillation

arXiv:2607.13124v1 Announce Type: cross Abstract: Structured pruning is a hardware-friendly way to compress LLMs, but it is mostly validated on multiple-choice recognition tasks, while the same compre

STOCKTAKE: Measuring the Gap Between Perception and Action in LLM Agents with a Fair Oracle

arXiv:2607.13618v1 Announce Type: new Abstract: LLM agents are increasingly evaluated on multi-week decision tasks in which the state that drives cost is never directly observed. On such tasks the fin

Tutorials

The Hitchhiker's Guide to Monoculture

arXiv:2607.13077v1 Announce Type: cross Abstract: Large language models (LLMs) often produce homogeneous outputs, raising concerns that AI coding assistants may lead to convergence in the software art

tutorialsarxiv-cs-ai

The Refusal Residue: When Probes Catch Alignment Faking and When They Don't

arXiv:2607.13346v1 Announce Type: cross Abstract: Alignment faking is dangerous because a model can appear compliant under monitoring while preserving behavior it would reveal when unmonitored. When n

TRACE: Turn-level Reward Assignment via Credit Estimation for Long-Horizon Agents

model-releasesarxiv-cs-lg

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

Track and Caption Any Motion: Open-Vocabulary Spatiotemporal Captioning via Trajectory-Conditioned Generation

arXiv:2512.10607v2 Announce Type: replace Abstract: We present TCAM (Track and Caption Any Motion), a generative framework that watches a video and with no text query and no region prompt decides what

safetyarxiv-cs-cv

Uncertainty-Aware Sequential Decision Rules for Event-Triggered LLM Invocation in Streaming Systems

arXiv:2607.13048v1 Announce Type: cross Abstract: Streaming inference pipelines increasingly pair lightweight fast models with Large Language Models (LLMs) that provide rich semantic understanding at

UniPhysGen: Unified Physical Grounding for Simulation-Ready 3D Assets

arXiv:2607.13586v1 Announce Type: new Abstract: Physically grounded 3D assets are increasingly important for embodied AI and robotic simulation. However, most existing 3D assets lack unified physical

WaterMoE: Expert-Routing-based Watermarking for High Fidelity and Efficiency

arXiv:2607.13099v1 Announce Type: cross Abstract: Large language models (LLMs) have achieved remarkable success but raise growing concerns about content provenance and misuse, motivating the need for

Affordance-Guided Diffusion Prior for 3D Hand Reconstruction

arXiv:2510.00506v2 Announce Type: replace Abstract: How can we reconstruct 3D hand poses when large portions of the hand are heavily occluded by itself or by objects? Humans often resolve such ambigui

researcharxiv-cs-cv

Agentic systems for breast cancer treatment recommendations

model-releasesarxiv-cs-cl

arXiv:2607.12051v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly being explored for clinical decision support, but their reliability in complex oncology treatment planning

AnySleep: a channel-agnostic deep learning system for high-resolution sleep staging in multi-center cohorts

arXiv:2512.14461v2 Announce Type: replace Abstract: Sleep is essential for health, yet studying its dynamics requires manual sleep staging, a labor-intensive step in research and clinical care. Across

researcharxiv-cs-lg

Applications

Atomic Units of X: The Compression Layer of Intelligence

arXiv:2607.12634v1 Announce Type: new Abstract: This paper proposes a theoretical framework for understanding intelligence as a process of atomic compression and compositional reuse. We argue that cog

applicationsarxiv-cs-ai

Beyond Parallel Tracking: Interactive Multi-Feature Fusion Drives Semantic Reconstruction from Non-invasive Brain Recordings

arXiv:2607.12071v1 Announce Type: new Abstract: Continuous semantic reconstruction from non-invasive neural recordings remains limited by the representational mismatch between semantic feature spaces

safetyarxiv-cs-cl

Can LLMs Write Reliable Rubrics? A Meta-Evaluation for Experiment Reproduction

arXiv:2607.12835v1 Announce Type: new Abstract: Rubric-based evaluation is a promising approach for assessing open-ended outputs from LLM-based research agents, particularly in paper reproduction, whe

safetyarxiv-cs-cl

Applications

Color Pass-Through via Camera-Display Coupling

arXiv:2607.12746v1 Announce Type: new Abstract: When a real-world scene is captured by a smartphone camera and viewed on its screen, the displayed image often differs noticeably from the original scen

applicationsarxiv-cs-cv

Do We Really Need Transformers for Global Spatial Information Extraction in Traffic Forecasting?

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

EFLUX: Elastic Multi-Robot Formation Navigation and Adaptation with Agentic LLMs

arXiv:2607.12050v1 Announce Type: new Abstract: Multi-robot teams operating in confined or cluttered environments must adapt both their formation geometry and group topology to navigate through comple

agentsarxiv-cs-ro

Epistemic Stance Flexibility Probing: Measuring Prompt-Conditioned Register Shift in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2607.12739v1 Announce Type: new Abstract: A language model may be asked either what experts believe about a contested claim or what it believes about the claim itself. A trustworthy conversation

Evidence Recomposition and Predictive Context Residualization for Visual Attribution in Multimodal Large Language Models

arXiv:2509.22415v3 Announce Type: replace-cross Abstract: Multimodal large language models (MLLMs) have achieved strong vision-language performance, yet their token-level visual evidence remains diffi

FairCoder: Probing LLM Bias in High-Stakes Decision Making via Coding Tasks

model-releasesarxiv-cs-cl

arXiv:2501.05396v3 Announce Type: replace Abstract: Large language models (LLMs) are increasingly used in high-stakes decisions such as hiring and college admissions, making their social bias a critic

Fine-Tuned Multi-Agent Framework for Detecting OCEAN in Life Narratives

arXiv:2607.12215v1 Announce Type: new Abstract: Accurately assessing personality from text is challenging because traits are latent, context-dependent, and often subtly expressed across long narrative

agentsarxiv-cs-cl

From Words to Widgets for Controllable LLM Generation

arXiv:2604.10925v2 Announce Type: cross Abstract: Natural language remains the predominant way people interact with large language models (LLMs). However, users often struggle to precisely express and

researcharxiv-cs-cl

Hardware

Globalized Constrained Stein Variational Inference for Diverse Feasible Robot Motion Planning

arXiv:2607.12732v1 Announce Type: new Abstract: Robot motion planning is inherently multimodal, yet classical planners typically return only a single solution. Probabilistic formulations address this

hardwarearxiv-cs-ro

Graph-Constrained Policy Learning for Extreme Clinical Code Prediction

arXiv:2607.11954v1 Announce Type: cross Abstract: Clinical code prediction maps unstructured discharge summaries to ICD-10-CM leaf codes in a large, sparse, and deeply hierarchical label space. Most s

How Query Visibility Changes KV-Cache Compression Rankings: A Matched-Budget Audit

arXiv:2607.11942v1 Announce Type: cross Abstract: KV-cache compression methods are predominantly evaluated with the query appended to the context before compression -- a query-aware protocol. Yet the

How to Realize Recursively Self-Improving Agents and Personal Singularity: A Goal-, Scope-, Tool-, and Benchmark-Driven Multi-Agent Architecture

arXiv:2607.12254v1 Announce Type: new Abstract: Large language model (LLM) agents can increasingly plan, use tools, maintain memory, and execute long-horizon tasks. These advances motivate two linked

IdeaTrail: Full-Process Agent Trajectories for Scientific Ideation

arXiv:2607.10144v2 Announce Type: replace Abstract: Scientific ideation unfolds over multiple stages, including literature search, paper reading, tool use, claim checking, cross-paper synthesis, brain

agentsarxiv-cs-ai

Instance-Enriched Semantic Maps for Visual Language Navigation

arXiv:2607.12630v1 Announce Type: cross Abstract: Visual Language Navigation (VLN) aims to enable an embodied agent to navigate complex environments by following natural language instructions. Recent

agentsarxiv-cs-cv

Internet of Agentic Things: Networked AI Agents for Closed-Loop IoT Orchestration

arXiv:2607.12662v1 Announce Type: new Abstract: The paper introduces the Internet of Agentic Things (IoAT), an architectural framework that integrates agentic AI, IoT, cyber-physical systems, Physical