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Can You Trust What You See? Human and AI Detection of Synthetic Legal Evidence

arXiv:2606.07613v1 Announce Type: cross Abstract: Visual evidence has long been treated as a reliable form of legal proof, but advances in artificial intelligence (AI) are undermining that assumption.

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CANS: Accelerating Multiuser Collaborative Edge Inference via Cooperative Autodidactic NeuroSurgeon

DGX agent

arXiv:2606.09175v1 Announce Type: cross Abstract: Recently, mobile edge computing (MEC)-enabled collaborative deep neural network (DNN) inference has emerged as a promising approach for delivering int

local-aiarxiv-cs-ai

9 Jun 2026

Capability-Aligned Hierarchical Learning for Tool-Augmented LLMs

arXiv:2606.09371v1 Announce Type: new Abstract: Tool learning enables LLMs to invoke external tools to accomplish tasks. Prior studies have demonstrated the effectiveness of a hierarchical structure:

Capacity, Not Format: Rethinking Structured Reasoning Failures

arXiv:2606.09410v1 Announce Type: new Abstract: Prior work treats structured output as a reasoning tax, but this framing is incomplete: the cost of formatting depends strongly on a model's spare capac

CapRL++: Unified Reinforcement Learning with Verifiable Rewards for Dense Image and Video Captioning

arXiv:2606.09393v1 Announce Type: new Abstract: Image and video captioning are fundamental tasks that bridge the visual and linguistic domains, playing a critical role in pre-training Large Vision-Lan

CAPruner: Conceptual-Adjacent Scene Graph Pruner for Enhancing 3D Spatial Reasoning of Large Language Models

arXiv:2606.07529v1 Announce Type: cross Abstract: Large language models (LLMs) have recently been applied to 3D vision-language (3D-VL) tasks, which require spatial reasoning to identify target object

CardioMorphNet: Cardiac Motion Prediction Using a Shape-Guided Bayesian Recurrent Deep Network

arXiv:2508.20734v2 Announce Type: replace Abstract: Accurate cardiac motion estimation from cine cardiac magnetic resonance (CMR) images is vital for assessing cardiac function and detecting its abnor

CARE: A Conformal Safety Layer for Medical Summarization

arXiv:2606.08969v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for medical summarization, but their outputs can omit medically important information and introduce

CATPO: Critique-Augmented Tree Policy Optimization

model-releasesarxiv-cs-lg

arXiv:2606.08346v1 Announce Type: cross Abstract: Reinforcement learning with verifiable rewards (RLVR) has become a dominant paradigm for improving the reasoning capabilities of large language models

Causal Agent Replay: Counterfactual Attribution for LLM-Agent Failures

arXiv:2606.08275v1 Announce Type: cross Abstract: When an LLM agent fails -- issues a refund it should not have, calls the wrong tool, leaks data -- existing tooling answers what happened (observabili

Causal Longitudinal Prior-Fitted Networks for Counterfactual Outcome Prediction

model-releasesarxiv-cs-lg

arXiv:2606.05797v2 Announce Type: replace Abstract: Longitudinal treatment decisions from multivariate time-series data require predicting potential outcomes under future treatment sequences in the pr

Causal Representation Learning from Network Data

arXiv:2509.01916v2 Announce Type: replace Abstract: Causal disentanglement from soft interventions is identifiable under the assumptions of linear interventional faithfulness and availability of both

researcharxiv-cs-lg

Causal Semantic Alignment for LLM-based Time Series Forecasting

arXiv:2606.08262v1 Announce Type: new Abstract: Recent advances in Large Language Models (LLMs) have opened new possibilities for time series forecasting by enabling alignment between temporal pattern

safetyarxiv-cs-lg

Causal Transfer in Medical Image Analysis

arXiv:2603.24388v2 Announce Type: replace Abstract: Medical imaging models frequently fail when deployed across hospitals, scanners, populations, or imaging protocols due to domain shift, limiting the

safetyarxiv-cs-cv

CausShield: Sample Reconstruction-Resilient Vertical FL via Causal Representation Learning

arXiv:2606.08027v1 Announce Type: cross Abstract: Vertical federated learning (VFL) is a distributed learning paradigm that leverages vertically partitioned features across isolated parties without sh

Chain of Flow: ECG-Conditioned 4D Cardiac Cine Generation from Patient-Specific Anatomical Anchor

arXiv:2602.22919v2 Announce Type: replace Abstract: Cardiac cine magnetic resonance imaging (MRI) is central to functional cardiac assessment, yet a full current cine sequence may not always be direct

Applications

Characterizing the Discrete Geometry of ReLU Networks

arXiv:2606.07728v1 Announce Type: new Abstract: It is well established that ReLU networks define continuous piecewise-linear functions, and that their linear regions are polyhedra in the input space.

applicationsarxiv-cs-lg

Cheap Reward Hacking Detection

arXiv:2606.08893v1 Announce Type: cross Abstract: A small transformer encoder is trained to map Terminal-Wrench trajectories onto a unit sphere where embedding distance approximates the L_1 distance b

Cherry-pick Override: Unsafe Directional Commitment in LLM Judges under Mixed Evidence

arXiv:2606.07834v1 Announce Type: cross Abstract: LLM judges increasingly turn verdicts into system commitments. Under mixed evidence (claims with both supporting and refuting sources) this is unsafe:

CheXanatomy: Anatomy-Aware Vision-Language Modeling for Chest Radiographs

arXiv:2606.08420v1 Announce Type: new Abstract: Vision-language models (VLMs) pretrained on large-scale image-text pairs demonstrate strong image-level understanding, but are primarily optimized for g

safetyarxiv-cs-cv

Chiaroscuro Attention: Spending Compute in the Dark

arXiv:2606.08327v1 Announce Type: cross Abstract: Standard transformers apply self-attention uniformly at every layer and token, regardless of whether the input requires dynamic cross-token interactio

CHIMERA-Bench: A Benchmark Dataset for Epitope-Specific Antibody Design

arXiv:2603.13431v3 Announce Type: replace-cross Abstract: Computational antibody design has seen rapid methodological progress, with dozens of deep generative methods proposed in the past three years,

ChinaHeritaQA: A Culturally-Grounded Visual Question Answering Dataset for World Heritage Sites in China

arXiv:2606.08959v1 Announce Type: new Abstract: We introduce ChinaHeritaQA, a multimodal benchmark dataset for evaluating the cultural reasoning abilities of vision-language models (VLMs) on UNESCO Wo

CHROMA: Detecting AI-Generated Images through Inter-Channel Color-Space Correlations

arXiv:2606.08864v1 Announce Type: new Abstract: The rapid adoption of diffusion and large-scale generative models has made it increasingly challenging to distinguish synthetic imagery from real photog

ChronoPhyBench: Do MLLMs Truly Understand the World or Merely Exploit Language Priors?

arXiv:2606.07962v1 Announce Type: new Abstract: Recent advancements in Multimodal Large Language Models (MLLMs) have demonstrated remarkable proficiency in open-world reasoning and understanding. Howe

CineDance: Towards Next-Generation Multi-Shot Long-Form Cinematic Audio-Video Generation

arXiv:2606.09639v1 Announce Type: new Abstract: The fidelity and structural diversity of training datasets fundamentally determine the capabilities of video generation models. While commercial systems

safetyarxiv-cs-cv

CLASP: Language-Driven Robot Skill Selection and Composition using Task-Parameterized Learning

arXiv:2606.08169v1 Announce Type: cross Abstract: Enabling robots to understand and execute tasks from natural language commands while maintaining data efficiency remains challenging. Foundation model

Classifying galaxies in the Galaxy10 DECals dataset using Inception and Residual CNNs

arXiv:2606.08826v1 Announce Type: new Abstract: Image data regarding galactic morphology is expected to increase both in quantity and quality for the next foreseeable years; thus it is important to ex

Claude Code-Driving Scenario Mining for the Argoverse 2 Challenge

arXiv:2606.09180v1 Announce Type: new Abstract: We present our submission to the CVPR 2026 Argoverse 2 Scenario Mining Challenge. Our system uses a four-stage pipeline: (1) autonomous code generation

Claw-R1: A Step-Level Data Middleware System for Agentic Reinforcement Learning

arXiv:2606.09138v1 Announce Type: new Abstract: Agentic reinforcement learning (RL) has become an important post-training paradigm for turning LLMs from static chatbots into interactive agents, giving

safetyarxiv-cs-lg

CLONE: A 3DGS-Based Closed-Loop Differentiable Optimization Framework for Single-Image Normal Estimation

arXiv:2508.05950v2 Announce Type: replace-cross Abstract: We propose CLONE, a 3DGS-based Closed-Loop differentiable Optimization framework for single-image Normal Estimation. The core idea is to const

Closing the Prior-Posterior Loop: Self-Reflective Molecular Design with Analysis-Driven LLM Iteration

arXiv:2606.09520v1 Announce Type: cross Abstract: Can a general-purpose large language model design molecules with the precision of a seasoned chemist? Current LLM-based frameworks answer this questio

Closing the Sim-to-Real Gap: An Evaluation Framework for Autonomous Cyber Defense Configuration of Commercial EDR

arXiv:2606.08168v1 Announce Type: cross Abstract: Leading commercial endpoint detection and response (EDR) products have shifted from operator-configured rule sets to multi-component systems where aut

Closure-Validated Circuit Discovery in Attention Heads: Co-activation Proposes, Ablation Disposes

arXiv:2606.09607v1 Announce Type: cross Abstract: Interpretability increasingly treats groups of components, not individual units, as the basic object, and proposes to find them by clustering co-activ

CLPO: Curriculum Learning meets Policy Optimization for LLM Reasoning

arXiv:2509.25004v2 Announce Type: replace Abstract: Online reinforcement learning with verifiable rewards (RLVR) has become an effective paradigm for improving the reasoning abilities of large languag

Coarse-to-Fine Hierarchical Alignment for UAV-based Human Detection using Diffusion Models

arXiv:2512.13869v3 Announce Type: replace Abstract: Training object detectors demands extensive, task-specific annotations, yet this requirement becomes impractical in UAV-based human detection due to

Code Is More Than Text: Uncertainty Estimation for Code Generation

arXiv:2606.09577v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed as code generators, where silently wrong programs pose real safety and reliability risks. Relia

safetyarxiv-cs-lg

CodeTaste: Can LLMs Generate Human-Level Code Refactorings?

arXiv:2603.04177v2 Announce Type: replace-cross Abstract: LLM coding agents can generate working code, but their solutions often accumulate complexity, duplication, and architectural debt. Human devel

Local Ai

Collaborative Edge-to-Server Inference for Vision-Language Models

arXiv:2512.16349v2 Announce Type: replace-cross Abstract: We propose a collaborative edge-to-server inference framework for vision-language models (VLMs) that reduces communication cost while maintain

local-aiarxiv-cs-ai

Agents

Collaborative Human-Agent Protocol (CHAP)

arXiv:2606.09751v1 Announce Type: new Abstract: Foundation models are moving from response generation into operational roles. They plan across steps, call tools, request human input, coordinate with o

agentsarxiv-cs-ai

Local Ai

Communication-Efficient Federated Learning under Dynamic Device Arrival and Departure: Convergence Analysis and Algorithm Design

arXiv:2410.05662v4 Announce Type: replace Abstract: Most federated learning (FL) approaches assume a fixed device set. However, real-world scenarios often involve devices dynamically joining or leavin

local-aiarxiv-cs-lg

Community-Specific Slang and Entity Detection via Semantic Shift in Fine-Tuned Language Models

arXiv:2606.07522v1 Announce Type: cross Abstract: We propose an unsupervised method of resolving slang, unique entities, and folklore from online communities by isolating words in the lexicon that hav

researcharxiv-cs-lg

Comparative evaluation of training strategies using partially labelled datasets for segmentation of white matter hyperintensities and stroke lesions in FLAIR MRI

arXiv:2601.20503v2 Announce Type: replace-cross Abstract: White matter hyperintensities (WMH) and ischaemic stroke lesions (ISL) are key imaging biomarkers of cerebral small vessel disease (SVD) detec

COMPASS: Complete Multimodal Fusion via Proxy Tokens and Shared Spaces for Ubiquitous Sensing

arXiv:2604.02056v2 Announce Type: replace Abstract: Missing modalities in multimodal sensing cause not only information loss but also a fusion-interface mismatch: a fusion head trained on a canonical

Applications

Complement or substitute? How AI increases the demand for human skills

arXiv:2412.19754v4 Announce Type: replace-cross Abstract: Artificial Intelligence (AI) is transforming the nature of work, yet there is limited empirical evidence on how it affects demand for human sk

applicationsarxiv-cs-ai

ComplexConstraints and Beyond: Expert Rubrics for RLVR

arXiv:2606.09118v1 Announce Type: new Abstract: As LLM capabilities advance rapidly, the evaluation methods used to assess them increasingly lag behind. Traditional benchmarks relied on programmatic v

Component Ablation for Efficient Hybrid Language Model Architectures: Performance, Resilience, and Compression Implications

arXiv:2603.22473v2 Announce Type: replace-cross Abstract: Hybrid language models combine softmax attention with linear-time sequence mechanisms such as state-space or linear-attention layers, but the

Compositional Approximation Can Strictly Outperform Superpositional Approximation

arXiv:2606.08727v1 Announce Type: cross Abstract: Many classically studied function classes are known to be approximated optimally by superpositional methods, i.e. with approximants constructed as the

researcharxiv-cs-lg