Search: “reasoning”

StackingNet: Collective Inference Across Independent AI Foundation Models

arXiv:2602.13792v2 Announce Type: replace Abstract: Artificial intelligence built on large foundation models has transformed language understanding, computer vision, and reasoning, yet these systems r

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TAP-VLA: Tactile Annotation Prompting for Vision Language Action Models

DGX agent

arXiv:2606.29089v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models demonstrate impressive reasoning over visual, semantic, and spatial task variations by leveraging large-scale vision

safetyarxiv-cs-ro

30 Jun 2026

The Effect of Scripts and Formats on LLM Numeracy

arXiv:2601.15251v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved impressive proficiency in basic arithmetic, rivaling human-level performance on standard numerical tasks.

researcharxiv-cs-cl

Agents

UnfoldArt: Zero-Shot Recovery of Full Articulated 3D Objects from Text or Image

arXiv:2606.30608v1 Announce Type: new Abstract: Articulated 3D objects are essential for interactive environments in embodied AI, robotics, and virtual reality, but reconstructing their structure and

agentsarxiv-cs-cv

When More Sampling Hurts: The Modal Ceiling and Correlation Ceiling of Test-Time Scaling

arXiv:2606.28661v1 Announce Type: cross Abstract: People overthink; language models over-sample, and the extra effort can talk both into a worse answer. Reasoning systems answer a hard question by sam

Applications

COCOLogic-V2: Identifying Logical Inconsistencies via Truly Hard-Negatives

arXiv:2606.28194v1 Announce Type: new Abstract: While interpretable models such as concept bottleneck models (CBMs) and program synthesis methods enable verification of model decisions, their evaluati

applicationsarxiv-cs-lg

Democratic ICAI: Debating Our Way to Steering Principles from Preferences

arXiv:2606.28294v1 Announce Type: new Abstract: Preference-based alignment often struggles to capture the reasoning that underlies human judgments. Many evaluations rely on multiple interacting criter

safetyarxiv-cs-lg

Dismantling Pathological Shortcuts: A Causal Framework for Faithful LVLM Decoding

arXiv:2606.27596v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) exhibit sophisticated reasoning but remain susceptible to object hallucination. Deviating from the prevailing att

Formalizing Latent Thoughts: Four Axioms of Thought Representation in LLMs

arXiv:2606.27378v1 Announce Type: new Abstract: We introduce an axiomatic evaluation framework for latent thought representations in LLMs, comprising metrics that are independent of downstream benchma

Agents

GraphPilot: Grounded Scene Graph Conditioning for Language-Based Autonomous Driving

arXiv:2511.11266v4 Announce Type: replace Abstract: Vision-language models have recently emerged as promising planners for autonomous driving, where success hinges on topology-aware reasoning over spa

agentsarxiv-cs-cv

HiMu: Hierarchical Multimodal Frame Selection for Long Video Question Answering

arXiv:2603.18558v2 Announce Type: replace-cross Abstract: Long-form video question answering requires reasoning over extended temporal contexts, making frame selection a critical bottleneck for multi-

Just Ask: Curious Code Agents Reveal System Prompts in Frontier LLMs

arXiv:2601.21233v2 Announce Type: replace Abstract: Autonomous code agents built on large language models are reshaping software and AI development through tool use, long-horizon reasoning, and self-d

Masked Language Flow Models

arXiv:2606.27617v1 Announce Type: new Abstract: Masked Diffusion Models (MDMs) promise fast, parallel language generation, but their reverse transition factorises across token positions -- an approxim

researcharxiv-cs-cl

Ontology-Guided Evidence Path Inference for Multi-hop Knowledge Graph Question Answering

arXiv:2606.28076v1 Announce Type: new Abstract: Knowledge graph question answering (KGQA) aims to answer natural-language questions by reasoning over structured facts. Existing multi-hop KGQA methods

SidConArena: An Environment Evaluating Agents in Open-Ended,Positive-Sum Bargaining Game

arXiv:2606.27397v1 Announce Type: cross Abstract: Evaluating LLM agents requires dynamic environments that go beyond static reasoning and zero-sum games. Real-world economic interaction is often open-

Understanding How MLLMs Describe Artworks Using Token Activation Maps

arXiv:2606.27947v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) describe artworks with remarkable fluency, yet the visual reasoning behind their outputs remains opaque. When a

researcharxiv-cs-cv

When Search Agents Should Ask: DiscoBench for Clarification-Aware Deep Search

arXiv:2606.27669v1 Announce Type: new Abstract: Search agents powered by large language models (LLMs) are increasingly used to solve complex information-seeking tasks, requiring multi-step retrieval a

A Process Harness for Uplifting Legacy Workflows to Agentic BPM: Design and Realization in CUGA FLO

arXiv:2606.27188v1 Announce Type: new Abstract: We introduce the process harness, a new mechanism for uplifting legacy workflows into Agentic Business Process Management (Agentic BPM) without replacin

Accelerating Returns and the Qualitative Engine for Science

arXiv:2606.26359v1 Announce Type: new Abstract: Ray Kurzweil described a thesis of accelerating returns, which is the most influential narratives in discussions of technological progress. Its central

Beyond Logical Forms: LLM-Extracted Patterns for Fallacy Classification

arXiv:2606.26698v1 Announce Type: cross Abstract: In today's fast-paced information era, logical fallacies, defined as defective patterns of reasoning, inevitably contribute to the growth of informati

Applications

Evaluation-Strategy Gap in Fault Diagnosis of Deep Learning Programs

arXiv:2606.26492v1 Announce Type: cross Abstract: Deep Learning (DL) programs can fail during training for many reasons, and diagnosing the cause is a costly and time-consuming maintenance task. Techn

applicationsarxiv-cs-ai

From Structure to Synergy: A Survey of Vision-Language Perception Paradigm Evolution in Multimodal Large Language Models

arXiv:2606.26196v1 Announce Type: cross Abstract: Multimodal Large Language Models (MLLMs) have recently made remarkable progress in unifying vision-language understanding and reasoning, especially fo

Local Ai

Joint Reward Modeling: Internalizing Chain-of-Thought for Efficient Visual Reward Models

arXiv:2602.07533v2 Announce Type: replace Abstract: Reward models are critical for reinforcement learning from human feedback, as they determine the alignment quality and reliability of generative mod

local-aiarxiv-cs-ai

Orthogonal Hierarchical Decomposition for Structure-Aware Table Understanding with Large Language Models

arXiv:2602.01969v2 Announce Type: replace Abstract: Complex tables with multi-level headers, merged cells and heterogeneous layouts pose persistent challenges for LLMs in both understanding and reason

researcharxiv-cs-cl

Paying More Attention to Visual Tokens in Self-Evolving Large Multimodal Models

arXiv:2606.27373v1 Announce Type: new Abstract: Recently, self-evolving large multimodal models (LMMs) have received attention for improving visual reasoning in a purely unsupervised setting. However,

safetyarxiv-cs-cv

Perception, Verdict, and Evolution: Hindsight-Driven Self-Refining Forensics Agent for AI-Generated Image Detection

arXiv:2606.26552v1 Announce Type: cross Abstract: The rapid advancement of generative models presents a significant challenge to existing deepfake detection methods, particularly given the widespread

PhyEditBench: A Real-World Multi-Stage Benchmark for Physics-Aware Image Editing

arXiv:2606.26551v1 Announce Type: new Abstract: While instruction-based image editing, enabled by multi-modal generative models, has advanced significantly, existing benchmarks lack a comprehensive ev

Qwen-Image-Agent: Bridging the Context Gap in Real-World Image Generation

arXiv:2606.26907v1 Announce Type: new Abstract: While text-to-image (T2I) models have achieved remarkable progress, they struggle with real-world requests that are often underspecified, implicit, or d

Agents

SKILL-DISCO: Distilling and Compiling Agent Traces into Reusable Procedural Skills

arXiv:2606.26669v1 Announce Type: new Abstract: Agents often repeatedly solve similar task instances from scratch, leading to unnecessary reasoning cost and long execution traces. Prior work has explo

agentsarxiv-cs-ai

TAVR-VLM: Risk-Conditioned Causal Grounding for Hallucination-Resistant Report Generation

arXiv:2606.26874v1 Announce Type: new Abstract: Transcatheter Aortic Valve Replacement (TAVR) planning requires meticulous multimodal reasoning. However, adapting Multimodal Large Language Models (MLL

TOPS: First-Principles Visual Token Pruning via Constructing Token Optimal Preservation Sets for Efficient MLLM Inference

arXiv:2606.27161v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) have achieved strong multimodal reasoning capabilities, but their efficiency is limited by the large number of

Visual-Language-Guided Task Planning for Horticultural Robots

model-releasesarxiv-cs-ro

arXiv:2601.11906v2 Announce Type: replace Abstract: Crop monitoring is essential for precision agriculture, but current systems lack high-level reasoning. We introduce a novel, modular framework that

Brevity is the Soul of Inference Efficiency: Inducing Concision in VLMs via Data Curation

arXiv:2606.25432v1 Announce Type: cross Abstract: Inference efficiency is typically pursued by shrinking the model: distillation, pruning, quantization, and sparse routing each lower per-token cost wh

researcharxiv-cs-cv

CausalRAG2: Hierarchical Causal Knowledge Graph Design for RAG

arXiv:2602.05143v2 Announce Type: replace Abstract: Retrieval augmented generation (RAG) has enhanced large language models by enabling access to external knowledge, with graph-based RAG emerging as a

Counterfeit Answers: Adversarial Forgery against OCR-Free Document Visual Question Answering

arXiv:2512.04554v2 Announce Type: replace Abstract: Document Visual Question Answering (DocVQA) enables end-to-end reasoning grounded on information present in a document input. While recent models ha

researcharxiv-cs-cv

Externalizing Research Synthesis and Validation in AI Scientists through a Research Harness

arXiv:2606.18874v2 Announce Type: replace Abstract: AI systems can increasingly automate scientific workflows, but the reasoning that links prior evidence, generated ideas, experiments and final claim

Tutorials

How Complexity Contributes to Learning Opacity in Machine Learning

arXiv:2606.24953v1 Announce Type: new Abstract: Machine learning (ML) algorithms are known to be opaque. We do not know the reasons for their predictions. The learning process leading to the predictio

tutorialsarxiv-cs-lg

Measurable Majorities Are Not Finitely Axiomatizable

arXiv:2606.25954v1 Announce Type: cross Abstract: This theoretical note studies the finite axiomatizability of strict majority reasoning in finite social decision frames. Moss and Pedersen (2026) intr

Multi-Stream Temporal Fusion for Financial Fraud Detection

model-releasesarxiv-cs-lg

arXiv:2606.25007v1 Announce Type: new Abstract: Financial fraud detection in digital banking requires reasoning over multiple heterogeneous event streams -- transactions, login sessions, risk signals

Position Spaces and Graphs

arXiv:2606.25719v1 Announce Type: new Abstract: In this paper, we introduce position graphs, a graph-based reasoning framework based on the formalization of position spaces. This framework utilizes tw

Small Initialization Matters for Large Language Models

arXiv:2606.17945v2 Announce Type: replace Abstract: Large language models provide a tractable system for asking how intelligence itself emerges, rather than only how LLMs can be engineered. Although p

SpeechEQ: Benchmarking Emotional Intelligence Quotient in Socially Aware Voice Conversational Models

arXiv:2606.25990v1 Announce Type: new Abstract: As multimodal conversational systems increasingly engage in spoken interaction, their ability to navigate paralinguistic social cues has become a critic

SSMNBench: Diagnosing Image-based Cross-View Human-Object Understanding via Single-View Sufficiency and Multi-View Necessity

arXiv:2606.25634v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have shown remarkable progress in single-image perception, yet their ability to reason about complex cross-view

SurgAtlas: A Large-Scale Surgical Video-Language Dataset with 2,391 Hours of Open and Minimally Invasive Surgery

arXiv:2606.25905v1 Announce Type: new Abstract: We introduce SurgAtlas, the largest surgical video-language dataset to date, comprising 15,291 videos (2,391 hours) spanning 18 surgical specialties and

Toten: A Knowledge-Based System For Structure-Preserving Representation Of Physical Quantities And Technical Notation In Brazilian Portuguese

arXiv:2606.19626v2 Announce Type: replace-cross Abstract: AI pipelines that reason quantitatively over technical text depend on input where physical quantities, numbers, units, and symbolic expression

Yuvion VL: A Multimodal Foundation Model for Adversarial Content and AI Safety

arXiv:2606.25034v1 Announce Type: new Abstract: General-purpose models often struggle to reliably identify and understand real-world multimodal risks, largely due to the inherent multimodal adversaria

safetyarxiv-cs-cv

An Introduction to Causal Reinforcement Learning

arXiv:2606.24160v1 Announce Type: new Abstract: Causal inference provides a set of principles and tools that allow one to combine data and knowledge about an environment to reason with questions of co

24 Jun 2026

Local Ai

An LMM for Precisely Grounding Elements in Documents