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CAER: Conflict-Aware Evidence Routing with Dual Prefix Experts for Multimodal Large Language Models

model-releasesarxiv-cs-cv

arXiv:2607.28991v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have demonstrated remarkable capabilities in multimodal understanding and generation. However, when textual inp

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Safety

CAGE: Certified Authorization under Typed-Return Uncertainty for Tool-Using Agents

DGX agent

arXiv:2607.29190v1 Announce Type: new Abstract: Tool-using LLM agents act on typed tool returns, records pairing provenance and categorical fields with numerical values. Runtime permission gates gener

safetyarxiv-cs-ai

3 Aug 2026

Applications

CalibratedRubric: Task-Adaptive Rubric Banks for Open-Ended LLM Evaluation

arXiv:2607.29252v1 Announce Type: cross Abstract: Reliable evaluation of open-ended LLM outputs requires fine-grained rubrics, yet expert curation is costly and difficult to scale. Existing automated

applicationsarxiv-cs-ai

CALM-AH: An ABAW11-Calibrated Multimodal Ensemble with Reliability-Gated Multi-Expert Consensus for Video-Level Ambivalence and Hesitancy Recognition

arXiv:2607.29310v1 Announce Type: new Abstract: Ambivalence and hesitancy (A/H) are subtle behavioural states that may be expressed through language, voice, facial activity, and other non-verbal cues.

researcharxiv-cs-cv

Can AI Evaluate AI Scientists? A Benchmarking Study of Autonomous Research Generation Systems Using Automated Multi-Model Review

arXiv:2607.28631v1 Announce Type: new Abstract: AI Scientist systems capable of autonomous research have the potential to significantly accelerate scientific discovery. However, evaluating and compari

Can Large Language Models Derive New Knowledge? A Dynamic Benchmark for Biological Knowledge Discovery

arXiv:2603.03322v2 Announce Type: replace-cross Abstract: Recent advancements in Large Language Model (LLM) agents have demonstrated remarkable potential in automatic knowledge discovery. However, rig

Can LLMs Really Understand Item Difficulty Levels? Implications for Automated Item Generation Using LLMs

model-releasesarxiv-cs-cl

arXiv:2607.28634v1 Announce Type: new Abstract: The estimation of item difficulty plays a key role in both formative assessment and large-scale high-stakes summative assessments. This study explores h

Can Synthetic Data Overcome the Generalization Limits of AI-Based Flower and Pod Detection Across Cowpea Breeding Genotypes and Environments?

arXiv:2607.28796v1 Announce Type: new Abstract: High-throughput phenotyping requires AI-enabled computer vision models that generalize across genotypes, locations, and growing seasons, yet such models

researcharxiv-cs-cv

Can Zero-Shot LLMs Predict Child Malnutrition? A Fairness and Temporal Robustness Study

arXiv:2607.29082v1 Announce Type: new Abstract: Child malnutrition remains a major public health challenge in low- and middle-income countries, particularly in South Asia, where early identification o

safetyarxiv-cs-cl

CBCT-IQ: A Publicly Available Annotated Cone-Beam CT Dataset for Image Quality Assessment and Benchmarking

model-releasesarxiv-cs-cv

arXiv:2607.29253v1 Announce Type: cross Abstract: Medical image quality plays a critical role in diagnostic accuracy, especially in X-ray-based imaging modalities such as cone-beam computed tomography

CENDRe: Concept Extraction with Natural Domain Representations

arXiv:2607.29621v1 Announce Type: cross Abstract: Convolutional neural networks (CNNs) are widely used for time-series classification, but their deployment in critical domains requires understanding t

local-aiarxiv-cs-ai

Chain-of-Models: Cross-Model Auditing for Bias-Robust LLM Judges

arXiv:2607.28636v1 Announce Type: new Abstract: LLMs increasingly serve as automated judges, but their judgments remain vulnerable to cognitive biases. Existing mitigations mostly rely on prompt-drive

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Choose What to Manipulate: Revealing Data Scaling Laws in Bounding-Box Guided Policies for Semantic Manipulation

model-releasesarxiv-cs-ro

arXiv:2602.11885v2 Announce Type: replace Abstract: Diffusion-based policies generalize poorly in semantic manipulation, a key obstacle to real-world deployment, because text-only instructions cannot

Classification of COVID-19 cases from chest CT volumes using hybrid model of 3D CNN and 3D MLP-Mixer

arXiv:2607.28978v1 Announce Type: new Abstract: This paper proposes an automated classification method of COVID-19 chest CT volumes using improved 3D MLP-Mixer. Novel coronavirus disease 2019 (COVID-1

local-aiarxiv-cs-cv

CLIFT: Turning Gemini Robotics On-Device into Humanoid Specialists via Non-Invasive Closed-Loop Iterative Fine-Tuning

arXiv:2607.29172v1 Announce Type: cross Abstract: While robot foundation models are growing increasingly capable, the strongest models are typically trained on proprietary data and remain closed-sourc

Agents

Code Is the Body: Agent-Owned Software Bodies for Recursive Evolution and Descent

arXiv:2607.28691v1 Announce Type: cross Abstract: Personalized AI agents are often configurable without giving users control over the artifacts that determine their future behavior. We present OurArk,

agentsarxiv-cs-ai

CoDe-SSM: Context-Detail Decoupled State Space Model for Efficient UHD Image Restoration

arXiv:2607.29595v1 Announce Type: new Abstract: Ultra-high-definition (UHD) image restoration must balance the aggregation of spatially recurring degradation cues with the preservation of localized im

local-aiarxiv-cs-cv

CodeRescue: Budget-Calibrated Recovery Routing for Coding Agents

arXiv:2607.19338v2 Announce Type: replace Abstract: Coding agents increasingly operate in executable environments where a failed attempt produces actionable feedback rather than merely an incorrect an

Agents

CodeShrink: Adaptive Visual Compression for Efficient Multimodal Code Understanding

arXiv:2607.29637v1 Announce Type: new Abstract: Rendering source code as images offers a promising way to reduce the input costs of Multimodal Large Language Models (MLLMs). Adjusting image resolution

agentsarxiv-cs-cv

Combining Large Language Models and Symbolic Reasoning for Multi-Robot Temporal Planning through Explainable Knowledge Bases

arXiv:2502.19135v2 Announce Type: replace Abstract: We present PLANTOR, a framework for generating and executing multi-robot task plans from natural-language task descriptions through LLM-assisted kno

Communication-Efficient Secure Aggregation in Decentralized Learning

model-releasesarxiv-cs-lg

arXiv:2405.07708v3 Announce Type: replace Abstract: Decentralized learning (DL) enables participants to collaboratively train models without a central server, yet it faces significant scalability chal

Compiled AI: Deterministic Code Generation for LLM-Based Workflow Automation

arXiv:2604.05150v2 Announce Type: replace-cross Abstract: We study compiled AI, a paradigm in which large language models generate executable code artifacts during a compilation phase, after which wor

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Conditioning Tree-Based Diffusions and Flows for Probabilistic Tabular Regression

arXiv:2607.28864v1 Announce Type: cross Abstract: Tree-based diffusion models fit flexible conditional predictive distributions for tabular regression without a neural density estimator, but they inhe

researcharxiv-cs-lg

ConnectED: A Curriculum-Aligned AI System for Vietnamese Instructional Lesson Planning and Student Learning

arXiv:2607.28647v1 Announce Type: cross Abstract: This paper presents ConnectED, a human-centered AI system that supports the full instructional lifecycle in Vietnamese education by linking curriculum

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COntExt: Towards Context-Aware Ontology Extension from Operational Metrics

arXiv:2607.29553v1 Announce Type: new Abstract: Organizations increasingly define operational metrics in structured, machine-readable formats to monitor systems, processes, and compliance. These metri

Tutorials

Contrastive Learning for Image Complexity Representation

arXiv:2408.03230v2 Announce Type: replace Abstract: Quantifying and evaluating image complexity can be instrumental in enhancing the performance of various computer vision tasks. Supervised learning c

tutorialsarxiv-cs-cv

Convergence and Regret of the Policy Gradient for Multi-Armed Bandits in Diffusion Environment

arXiv:2607.29593v1 Announce Type: new Abstract: This paper studies the policy gradient update for a multi-arm bandit problem in diffusion environment that is described by a stochastic differential equ

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Tutorials

Copy Less, Ground More: Overcoming Repetitive Copying in Long-Context Reasoning via Evidence-Aware Reinforcement Learning

arXiv:2607.19345v2 Announce Type: replace-cross Abstract: Large language models that generate step-by-step reasoning traces have achieved strong performance on complex tasks, and extending them to lon

tutorialsarxiv-cs-ai

CorrelationFlow: A Training-Free Geometric Approach for LiDAR Scene Flow Estimation

arXiv:2607.29237v1 Announce Type: new Abstract: LiDAR scene flow estimation has settled into a monoculture: nearly all recent methods share the same feed-forward architecture and the same family of se

researcharxiv-cs-cv

COSI-Lab: Conference Living Lab for Modeling Multi-Perspective Multimodal Social Intention

arXiv:2607.28649v1 Announce Type: cross Abstract: COSI-Lab presents a multimodal, multi-sensor dataset of an interdisciplinary scientific workshop containing 32 academics at an international conferenc

CPInj: Uncovering Prompt Injection Risks in Textual Collaborative Prompt Optimization

arXiv:2607.18622v2 Announce Type: replace-cross Abstract: Textual Collaborative Prompt Optimization (TCPO) extends TextGrad (Yuksekgonul et al., 2025) to a decentralized setting by allowing multiple c

local-aiarxiv-cs-ai

Cross-Lingual Transfer for Machine Translation in Turkic Languages

arXiv:2607.29355v1 Announce Type: cross Abstract: Cross-lingual transfer is central to low-resource machine translation, but its behavior within closely related language families remains insufficientl

Cross-Resolution Semantic Learning for Graph Domain Adaptation

arXiv:2607.29365v1 Announce Type: new Abstract: Graph Domain Adaptation (GDA) transfers predictive knowledge from labeled source graphs to unlabeled target graphs under distribution shift. Existing me

researcharxiv-cs-lg

Curriculum Matters: Data-Efficient Relational PFN Pretraining with Synthetic Data

model-releasesarxiv-cs-lg

arXiv:2607.29120v1 Announce Type: new Abstract: Relational Prior-Data Fitted Networks (PFNs) such as RDB-PFN approximate Bayesian inference over multi-table relational databases by pretraining on mill

D-VLC: Decentralized Vision-Language Collaboration for Heterogeneous Embodied Multi-Robot Systems in Unknown Environments

arXiv:2607.29009v1 Announce Type: new Abstract: Multi-robot systems, particularly heterogeneous robot swarms, can improve the efficiency of complex task execution through parallel collaboration and co

researcharxiv-cs-ro

DART: Dual-Axis Airborne Reachability-Gated Torque-Reaction for Off-Road Vehicle Jumps

model-releasesarxiv-cs-ro

arXiv:2607.29011v1 Announce Type: new Abstract: Traversing crests, ledges, and ditches at high speed often launches vehicles into the air, and a mishandled landing presents a substantial crash hazard.

DASH-OPD: Discrepancy-Aware Switching with Hysteresis for On-Policy Distillation

model-releasesarxiv-cs-lg

arXiv:2607.29078v1 Announce Type: new Abstract: On-policy distillation (OPD) trains student models on their own rollouts to reduce exposure bias. However, in multi-turn agent scenarios, early student

Data Turnstile: A Scalable Open Framework for Function-Calling Data Generation

model-releasesarxiv-cs-cl

arXiv:2607.29250v1 Announce Type: new Abstract: Small language models (SLMs) are attractive for agentic deployment due to low latency, reduced cost, and on-device privacy, yet they struggle with tool-

Deconstructing Off-Policy Ratios: Entropy-Scaled Trust Regions for Asynchronous Reinforcement Learning

arXiv:2607.22186v2 Announce Type: replace Abstract: Asynchronous reinforcement learning (RL) accelerates large language model (LLM) post-training by overlapping rollout generation with policy optimiza

local-aiarxiv-cs-ai

Deformable Medical Image Registration with KAN-based Implicit Neural Representations

arXiv:2509.22874v2 Announce Type: replace Abstract: Deformable image registration (DIR) is central to medical image analysis, supporting spatial alignment for longitudinal studies and multi-modal fusi

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Hardware

DeltaServe: Host-Agnostic Co-Serving of Inference and Fine-Tuning for LLMs

arXiv:2607.28848v1 Announce Type: cross Abstract: LLM serving systems are provisioned for peak load to meet strict latency targets, leaving substantial GPU compute idle whenever traffic falls below pe

hardwarearxiv-cs-lg

Demystifying Entropy-based Selection for Chain-of-Thought Compression in Large Reasoning Models

arXiv:2607.28707v1 Announce Type: new Abstract: Entropy-based pruning has been proposed as an effective method for compressing Chain-of-Thought (CoT) reasoning with negligible accuracy loss. We test t

researcharxiv-cs-cl

Dense Temporal Contrast Synthesis via Conditioned Latent Transport

arXiv:2607.29394v1 Announce Type: cross Abstract: Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is essential for breast cancer management, but reliance on gadolinium-based contrast ag

Design Concept: Scaffolding Geopolitical Reflection Among Tech Workers

arXiv:2607.28904v1 Announce Type: cross Abstract: This paper presents a speculative Human-Computer Interaction design proposal for encouraging geopolitical reflexivity amongst tech workers at geopolit

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Detecting AI-Generated Videos with Spiking Neural Networks

arXiv:2605.05895v2 Announce Type: replace-cross Abstract: Modern AI-generated videos are photorealistic at the single-frame level, leaving inter-frame dynamics as the main remaining axis for detection

Detecting Experiential Intertextuality Across Migration Routes: Beyond Surface Similarity in French Narratives

model-releasesarxiv-cs-cl

arXiv:2607.29188v1 Announce Type: new Abstract: Migrants traversing geographically distinct routes such as the Trans-Saharan and Balkan corridors often recount strikingly parallel lived experiences: p

Development of FDD-ON: an Ontology for VAV HVAC System Fault Detection and Diagnostics

arXiv:2607.29657v1 Announce Type: new Abstract: Fault detection and diagnosis (FDD) technology is essential for improving HVAC system reliability, energy efficiency, and maintenance effectiveness. How

DFSC: Error-Controlled Differentiable Mittag-Leffler Propagation for Fractional Scientific Machine Learning

arXiv:2607.29038v1 Announce Type: new Abstract: Fractional scientific machine learning requires numerical operators that can be differentiated, batched, accelerated, and composed with neural networks.

local-aiarxiv-cs-lg