Search: “reasoning”

MVDGC: Joint 3D and 2D Multi-view Pedestrian Detection via Dual Geometric Constraints

arXiv:2607.00273v1 Announce Type: new Abstract: The core challenge in multi-view pedestrian detection (MVPD) lies in effective aggregation of visual features from different viewpoints for robust occlu

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NOVA: Next-step Open-Vocabulary Autoregression for 3D Multi-Object Tracking in Autonomous Driving

DGX agent

arXiv:2603.06254v2 Announce Type: replace Abstract: Generalizing across unknown targets is critical for open-world perception, yet existing 3D Multi-Object Tracking (3D MOT) pipelines remain limited b

agentsarxiv-cs-cv

2 Jul 2026

Planning over MAPF Agent Dependencies via Multi-Dependency PIBT

arXiv:2603.23405v2 Announce Type: replace-cross Abstract: Modern Multi-Agent Path Finding (MAPF) algorithms must plan for hundreds to thousands of agents in congested environments within a second, req

Prompting GPT-5 on Scrum Certification Questions: An Empirical Accuracy Study

arXiv:2607.00049v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly used in Agile Software Development for documentation, coaching, and training. As practitioners adopt the

QuasiMoTTo: Quasi-Monte Carlo Test-Time Scaling

arXiv:2607.01179v1 Announce Type: cross Abstract: Scaling inference compute, by generating many parallel attempts per problem, is a costly but reliable lever for improving language model capabilities.

safetyarxiv-cs-cl

Rethinking Visual Privacy: A Compositional Privacy Risk Framework for Severity Assessment with VLMs

arXiv:2603.21573v2 Announce Type: replace Abstract: Existing visual privacy benchmarks largely treat privacy as a binary property, labeling images as private or non-private based on visible sensitive

Right in the Right Way: LM Training with Verifiable Rewards and Human Demonstrations

arXiv:2607.01181v1 Announce Type: cross Abstract: RL with verifiable rewards (RLVR) has emerged as a powerful paradigm for training LMs on tasks with well-defined success metrics, such as code generat

Safe Alone, Unsafe Together: Safeguarding Against Implicit Toxicity When Benign Images Combine

arXiv:2607.00576v1 Announce Type: new Abstract: Multi-image content has become an increasingly prevalent form of visual communication in social media, giving rise to a new safety issue, multi-image im

safetyarxiv-cs-cl

Seed2.0 Model Card: Towards Intelligence Frontier for Real-World Complexity

arXiv:2607.00248v1 Announce Type: new Abstract: We present Seed2.0, a model series that takes a meaningful step toward solving complex, real-world tasks. Our approach begins with identifying users' ge

applicationsarxiv-cs-ai

Shapley in Context: Explaining Financial Language with Domain Expertise

arXiv:2607.00856v1 Announce Type: cross Abstract: In recent years, large language models have achieved remarkable success and have seen growing adoption in financial applications. At the same time, ex

applicationsarxiv-cs-lg

SlowBA: An efficiency backdoor attack towards VLM-based GUI agents

arXiv:2603.08316v3 Announce Type: replace-cross Abstract: Modern vision-language-model (VLM) based graphical user interface (GUI) agents are expected not only to execute actions accurately but also to

agentsarxiv-cs-cl

Structured 4D Latent Predictive Model for Robot Planning

arXiv:2607.01166v1 Announce Type: cross Abstract: Video predictive models are emerging as a powerful paradigm in robotics, offering a promising path toward task generalization, long-horizon planning,

applicationsarxiv-cs-cv

SWE-Doctor: Guiding Software Engineering Agents with Runtime Diagnosis from Multi-Faceted Bug Reproduction Tests

arXiv:2607.00990v1 Announce Type: cross Abstract: Large language model (LLM)-based software engineering agents are increasingly developed to resolve software issues by generating patches from issue re

Understanding How Humans Inject Knowledge into Machine Learning Workflows through Visual Analytics

model-releasesarxiv-cs-lg

arXiv:2607.00969v1 Announce Type: cross Abstract: Visual analytics (VA) plays an increasingly important role in supporting machine learning (ML) workflows. In the field of visualization, such approach

Understanding Large Language Models

arXiv:2607.01006v1 Announce Type: new Abstract: Large Language Models (LLMs) represent one of the most significant advances in AI and natural language processing in recent years. Still, many pressing

researcharxiv-cs-cl

UniDrive-WM: Unified Understanding, Planning and Generation World Model for Autonomous Driving

arXiv:2601.04453v4 Announce Type: replace Abstract: World models have become central to autonomous driving, where accurate scene understanding and future prediction are crucial for safe control. Recen

When AI Agents Compete for Jobs: Strategic Capabilities and Economic Dynamics of AI Labour Markets

arXiv:2512.04988v2 Announce Type: replace-cross Abstract: Emerging agentic marketplaces provide the economic infrastructure for matching and coordinating the large amounts of AI agents used in agentic

ZO-Act: Efficient Zeroth-Order Fine-Tuning via One-Shot Activation-Informed Low-Rank Subspaces

model-releasesarxiv-cs-lg

arXiv:2607.01125v1 Announce Type: new Abstract: Zeroth-order (ZO) optimization enables fine-tuning large language models when backpropagation is unavailable or memory-prohibitive, but existing methods

Adaptive Cluster-First Route-Second Decomposition for Industrial-Scale Vehicle Routing

arXiv:2606.31820v1 Announce Type: new Abstract: Large-scale capacitated vehicle routing problems (CVRPs) are commonly addressed using cluster-first route-second (CFRS) approaches that split a routing

ALM2Vec: Learning Audio Embeddings for Universal Audio Retrieval with Large Audio-Language Models

arXiv:2606.30682v1 Announce Type: cross Abstract: Recent advances in language--audio retrieval have been largely driven by contrastive dual-encoder architectures that align audio and text in a shared

An Agentic AI Framework to Accelerate Scientific Discovery in Plant Phenotyping

arXiv:2606.31831v1 Announce Type: new Abstract: High-throughput plant phenotyping now generates image derived datasets far faster than scientists can analyze them. At Oak Ridge National Laboratory's A

BayesBench: Evaluating LLM Belief Trajectories Under Multi-Turn Evidence Accumulation

arXiv:2606.30850v1 Announce Type: new Abstract: Large language models (LLMs) are typically deployed in multi-turn conversations, where each turn provides new evidence that should reduce epistemic unce

Benchmarking Large Language Models on Floating-Point Error Classification

arXiv:2606.31308v1 Announce Type: new Abstract: This paper investigates the capability of Large Language Models (LLMs) to detect and classify floating-point errors statically in software code. We intr

Beyond But-for Test: Counterfactual Explanation in Abstract Argumentation via Actual Causality (Extended Version)

arXiv:2606.31080v1 Announce Type: cross Abstract: Counterfactual explanation in abstract argumentation calls for an answer to the what-if query: would the topic argument still be accepted if the statu

Compositional Concept-Based Neuron-Level Interpretability for Deep Reinforcement Learning

arXiv:2502.00684v2 Announce Type: replace-cross Abstract: Deep reinforcement learning (DRL) has successfully addressed many complex control problems. However, the neural networks representing policies

Contrastive Reflection for Iterative Prompt Optimization

arXiv:2606.30840v1 Announce Type: new Abstract: LLM agents are becoming central to information retrieval: they issue retrieval queries, synthesize answers, and increasingly serve as judges for IR eval

DISCOVER: A Solver for Distributional Counterfactual Explanations

arXiv:2603.16436v2 Announce Type: replace Abstract: Counterfactual explanations (CE) explain model decisions by identifying input modifications that lead to different predictions. Most existing method

safetyarxiv-cs-lg

DVG-WM: Disentangled Video Generation Enables Efficient Embodied World Model for Robotic Manipulation

arXiv:2606.32028v1 Announce Type: new Abstract: Video-based embodied world models provide an appealing substrate for robotic manipulation by predicting future states, yet current approaches remain lim

applicationsarxiv-cs-ro

Explicit Fuzzy Logic in the Feed-Forward Layer: Self-Forgetting Quantifiers Discover Legible Grammatical-Licensing Detectors

model-releasesarxiv-cs-cl

arXiv:2606.31845v1 Announce Type: new Abstract: A transformer's feed-forward (FFN) sublayer materializes the distinctions attention gathers, yet gives no account of what it computes. In a parameter-ne

From Failure to Alignment: A Requirements Engineering Framework for Machine Learning Systems

arXiv:2606.31589v1 Announce Type: cross Abstract: Organisations designing, developing, and deploying machine learning systems (MLS) need to be able to check that these systems are trustworthy, and com

safetyarxiv-cs-lg

From Search to Synthesis: Training LLMs as Zero-Shot Workflow Generators

arXiv:2606.30704v1 Announce Type: cross Abstract: Large language models (LLMs) excel across a wide range of tasks, yet their instance-specific solutions often lack the structural consistency needed fo

Generative Skill Composition for LLM Agents

model-releasesarxiv-cs-cl

arXiv:2606.32025v1 Announce Type: new Abstract: Recent LLM agents benefit from skills for solving complex tasks. Skills encapsulate modular packages of procedural knowledge and instructions for perfor

Geometry-Preserving Orthonormal Initialization for Low-Rank Adaptation in RLVR

arXiv:2606.31813v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) and its variants enable parameter-efficient fine-tuning of large language models under the supervised fine-tuning (SFT) par

Local Ai

Gradient Smoothing: Coupling Layer-wise Updates for Improved Optimization

arXiv:2606.30813v1 Announce Type: cross Abstract: Deep neural networks with repeated architectural blocks, such as transformers, often exhibit structured relationships across layers that emerge during

local-aiarxiv-cs-ai

Improved Upper Bounds for Slicing the Hypercube

arXiv:2602.16807v2 Announce Type: replace Abstract: A collection of hyperplanes H slices all edges of the n-dimensional hypercube Q_n with vertex set {-1,1}^n if, for every edge e in the hypercube, th

Investigating Multi-Agent Deliberation in Law

arXiv:2606.30906v1 Announce Type: new Abstract: Artificial Intelligence is increasingly applied to the field of law, and has the potential to increase access to justice. One particular movement that i

Measuring Judgment Quality in Natural-Language Explanations: Evidence from Forecasting Tournaments

arXiv:2606.30987v1 Announce Type: new Abstract: Decision-makers routinely rely on expert judgments accompanied by written explanations, yet explanation quality is difficult to measure at scale. Foreca

researcharxiv-cs-cl

MS-Resampler: Multi-Scope Visual Resampling for Efficient Multimodal LLMs

arXiv:2606.31383v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) typically employ resampling-based projectors to transform dense visual features into a compact token sequence f

Multimodal Benchmark for Safety Assessment in Industrial Inspection Scenarios

arXiv:2601.21173v2 Announce Type: replace-cross Abstract: With the rapid development of industrial intelligence and unmanned inspection, reliable perception and safety assessment for AI systems in com

MV-GEL: Language-Driven Multi-View Geometric Entity Localization on Meshes

arXiv:2606.31533v1 Announce Type: new Abstract: Identifying and grounding precise geometric entities, such as edges, planar regions, and curved surfaces within 3D objects, is foundational to computer-

No Place to Hide: Benchmarking Video Hallucination with Background-Controlled Pairs

arXiv:2606.31933v1 Announce Type: new Abstract: We introduce VidPair-Halluc, a new benchmark for evaluating video hallucination in large video models (LVMs) under rigorous and controlled conditions. U

Personalizing Marketplace Policies with Competing Objectives and Constrained Experiments: Evidence from a Job Marketplace

arXiv:2606.30932v1 Announce Type: new Abstract: Two-sided marketplaces connect distinct user groups whose interests often conflict -- improving outcomes on one side could degrade the other side's expe

safetyarxiv-cs-lg

{Phi}eat: Physically Grounded Material Feature Representation

arXiv:2511.11270v2 Announce Type: replace Abstract: While foundation models have emerged as general-purpose visual backbones, their representations are primarily optimized for semantics and lack expli

Random Reshuffling Dominates Stochastic Gradient Descent

arXiv:2606.32005v1 Announce Type: cross Abstract: Stochastic Gradient Descent (extsf{SGD}) is one of the most classical optimization algorithms with favorable theoretical guarantees, yet the practical

researcharxiv-cs-lg

Scientific Explanations in Health Sciences: Causality, Trust, and Epistemic Adequacy

arXiv:2606.31616v1 Announce Type: new Abstract: Medical Artificial Intelligence (AI) is widely expected to transform clinical practice, yet the decision-making processes of many Machine Learning (ML)

SimpleSearch-VL: A Simple Recipe for Multimodal Agentic Deep Search

arXiv:2606.31504v1 Announce Type: new Abstract: We present SimpleSearch-VL, an efficient, reliable, and practical framework for multimodal agentic search. Its core idea is to improve the agent's own s

StemVLA:An Open-Source Vision-Language-Action Model with Future 3D Spatial Geometry Knowledge and 4D Historical Representation

arXiv:2602.23721v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models integrate visual observations and language instructions to predict robot actions, demonstrating promising

Streaming Gaussian Encoding for 4D Panoptic Occupancy Tracking

arXiv:2606.30754v1 Announce Type: new Abstract: Camera-based 4D panoptic occupancy tracking (4D-POT) is a promising paradigm for holistic scene understanding from multi-view imagery, enabling joint re