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arXiv:2603.23115v2 Announce Type: replace Abstract: The realism of AI-generated images (AIGI) poses increasing challenges for reliable forensic detection, where heterogeneous expert detectors may prod

agentsarxiv-cs-cv

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Agentic Retrieval-Augmented Generation for Financial Document Question Answering

DGX agent

arXiv:2605.05409v2 Announce Type: replace Abstract: Financial document question answering (QA) demands complex multi-step numerical reasoning over heterogeneous evidence--structured tables, textual na

model-releasesarxiv-cs-ai

7 Jul 2026

AgentLTL: A Trace-Verification Framework for Measuring, Enforcing, and Training Procedural Compliance in Tool-Using LLM Agents

arXiv:2607.02599v1 Announce Type: cross Abstract: Tool-using LLM agents are usually evaluated by final-answer correctness or LLM judges. Neither captures how an answer was produced. In safety-critical

Air-Plan: Query-Optimized Topology Selection for Over-the-Air Decentralized Federated Learning

arXiv:2607.04254v1 Announce Type: cross Abstract: Over-the-air (OTA) aggregation exploits the superposition property of wireless multiple-access channels to aggregate model updates from multiple devic

researcharxiv-cs-lg

Alignment-Guided Largest Table Overlap Size Estimation

arXiv:2607.03049v1 Announce Type: new Abstract: Fast estimation of the size of the largest overlap between tables enables blocking and query-by-table retrieval in large table repositories. The first a

safetyarxiv-cs-cl

Amortising Bayesian Experimental Design for Sequential Information Gathering in LLMs

arXiv:2607.03426v1 Announce Type: cross Abstract: Large language models (LLMs) exhibit strong reasoning and world-knowledge capabilities, yet often struggle to gather information effectively across th

AnchorDream: Repurposing Video Diffusion for Embodiment-Aware Robot Data Synthesis

arXiv:2512.11797v2 Announce Type: replace-cross Abstract: The collection of large-scale and diverse robot demonstrations remains a major bottleneck for imitation learning, as real-world data acquisiti

safetyarxiv-cs-cv

Anchored Self-Play for Code Repair

model-releasesarxiv-cs-cl

arXiv:2607.03523v1 Announce Type: cross Abstract: Code repair is an important capability for language models (LMs): given a buggy program and unit tests, an LM must produce a fixed program that passes

AnchorSplat: Fast and Structure Consistent Detail Synthesis for Gaussian Splatting

arXiv:2607.01290v2 Announce Type: replace Abstract: 3D Gaussian Splatting (3DGS) has emerged as a powerful representation for high-fidelity rendering. However, existing assets often suffer from qualit

AnchorVLA: Bridging Discrete Decisions and Continuous Trajectories for Vision-Language-Action Planning

arXiv:2607.03182v1 Announce Type: cross Abstract: Autonomous driving planning requires translating navigation intent, traffic rules, dynamic interactions, and language instructions into executable con

APEX: Approximate-but-exhaustive search for ultra-large combinatorial synthesis libraries

model-releasesarxiv-cs-lg

arXiv:2510.24380v2 Announce Type: replace Abstract: Make-on-demand combinatorial synthesis libraries (CSLs) like Enamine REAL have significantly enabled drug discovery efforts. However, their large si

Attention Dynamics in Diffusion Models: A Visual Analytics Framework for Human-AI Collaboration

arXiv:2607.02563v1 Announce Type: cross Abstract: Diffusion-based text-to-image models can synthesize complex and highly structured visual content, yet the emergence and evolution of semantic structur

AudioX-Turbo: A Unified Framework for Efficient Anything-to-Audio Generation

arXiv:2606.12555v2 Announce Type: replace-cross Abstract: Audio and music generation based on flexible multimodal control signals is a widely applicable topic, with the following key challenges: 1) a

Local Ai

AULLM++: Structured-Token-Conditioned Large Language Models for Micro-Expression Action Unit Detection

arXiv:2603.08387v2 Announce Type: replace Abstract: Micro-expression Action Unit (AU) detection identifies localized AUs from subtle facial muscle activations, providing a foundation for decoding affe

local-aiarxiv-cs-cv

Auto: The AGI Compiler

arXiv:2607.04542v1 Announce Type: cross Abstract: Every LLM agent run re-derives its behavior token by token on a frontier model: brilliant, expensive, slow, and unbounded. We present Auto, a compiler

AutoCedar: An Agentic Framework for Verifier-Guided Access Control Policy Synthesis

arXiv:2607.03656v1 Announce Type: cross Abstract: Large Language Models are increasingly used to turn natural-language requirements into code. In access control, that shortcut is dangerous: a generate

AutoResearch: An Execution-Grounded Multi-Agent Framework for Reliable Research Workflow Automation

arXiv:2607.02520v1 Announce Type: cross Abstract: Automated research agents increasingly generate code, retrieve literature, and draft scientific artifacts, but they often fail to verify whether gener

AViS-Mamba: Adaptive Visual Steering of Audio State-Space Dynamics for Violence Detection

arXiv:2604.03329v2 Announce Type: replace-cross Abstract: Automatic violence detection from video is challenging because violent interactions may be distant, occluded, or only partially visible. Audio

safetyarxiv-cs-ai

Back to Basics: Improving Molecular Understanding in LLMs via SMILES-Graph Translation

arXiv:2607.03007v1 Announce Type: cross Abstract: Recent advances in molecular large language models have led to strong performance on molecular understanding and generation tasks, yet these gains oft

Banger compression paper from NVIDIA. (bookmark it) Bigger MoE models keep winning on quality, but serving them at interactive latency is st…

Banger compression paper from NVIDIA. (bookmark it) Bigger MoE models keep winning on quality, but serving them at interactive latency is still hard. NVIDIA compresses the hybrid MoE Nemotron-3-Super

model-releasesdair-ai--x

Best-of-Better-N: Generating Pre-Aligned Responses with In-Context Learning

arXiv:2607.03453v1 Announce Type: cross Abstract: Inference-time alignment methods, such as Best-of-N, offer a flexible alternative to training-based alignment by using reward models to select high-qu

safetyarxiv-cs-ai

Beyond Forecasting: The Belief-to-Trade Layer in Prediction-Market Agents

arXiv:2607.03015v1 Announce Type: new Abstract: Forecasting future events has attracted growing attention as a testbed for general-purpose AI. A natural way to ground this evaluation is let the models

Beyond Post-Quantization: Native Hash Learning with a Dedicated HASH Token

arXiv:2607.03328v1 Announce Type: new Abstract: Efficient large-scale image retrieval requires compact representations that preserve semantic similarity under fast Hamming-space search. Deep hashing i

researcharxiv-cs-cv

Beyond Task Completion: A Verification-vs.-Conformance Gap in Tool-Evolving Agents

arXiv:2604.00392v2 Announce Type: replace-cross Abstract: Agents that synthesize their own tools ship a second artifact alongside each answer: a software library that future tasks reuse, compose, and

Agents

Biological Motifs for Agentic Control

arXiv:2607.04240v1 Announce Type: new Abstract: The transition of Large Language Models (LLMs) from passive generators to autonomous agents has introduced significant challenges in reliability, securi

agentsarxiv-cs-ai

Brand-as-Memory: Vision-Language Models Encode Causal, Mechanistically Localizable Credibility Priors for News Sources

arXiv:2607.03365v1 Announce Type: cross Abstract: Vision-language models (VLMs) increasingly read news and web content as images, where the publisher's identity is visually present. We show that VLMs

Bridging Interleaved Multi-Modal Reasoning as a Unified Decision Process

arXiv:2607.03748v1 Announce Type: new Abstract: Unified multi-modal models (UMMs) have shown promising interleaved text-image reasoning capabilities, yet effectively optimizing such multi-turn generat

safetyarxiv-cs-ai

ChainReaction: Causal Chain-Guided Reasoning for Modular and Explainable Causal-Why Video Question Answering

arXiv:2508.21010v3 Announce Type: replace-cross Abstract: Existing Causal-Why Video Question Answering (VideoQA) models often struggle with higher-order reasoning, relying on opaque, monolithic pipeli

Chasing Moving Targets with Online Self-Play Reinforcement Learning for Safer Language Models

model-releasesarxiv-cs-cl

arXiv:2506.07468v4 Announce Type: replace-cross Abstract: Conventional large language model (LLM) safety alignment relies on a reactive, disjoint loop: attackers exploit a static model, then defenders

ChatImage: Navigating Long-Form LLM Answers through Interactive Images

arXiv:2607.05290v1 Announce Type: new Abstract: Large Language Models (LLMs) can produce detailed answers to complex queries, but these answers are typically presented as dense linear text, which make

Chronos: The AI Co-Historian

arXiv:2604.03553v2 Announce Type: replace Abstract: AI is increasingly supporting, accelerating, and automating scientific discovery across subjects. Yet, the adoption of AI in historical research rem

Applications

CIPHER: Causal Intervention Pathways for Healthcare Equity and Robustness

arXiv:2607.02596v1 Announce Type: new Abstract: Deep learning models for medical diagnosis frequently exhibit substantial performance disparities across sensitive subgroups (e.g., race, sex), even whe

applicationsarxiv-cs-cv

CLEAR: Closed-Loop Reinforcement Learning at Scale for End-to-End Autonomous Driving

arXiv:2607.02841v1 Announce Type: cross Abstract: End-to-end autonomous driving (E2E-AD) aims to directly map raw sensor information to driving actions. Recently, with the rapid advancement of multi-m

safetyarxiv-cs-cv

CodeJeNN: A simple C++ neural network generator for physics applications

arXiv:2607.02746v1 Announce Type: cross Abstract: Machine learning has shown speedups for numerical methods in physics applications, but integrating Python-based libraries into high-performance C++ so

researcharxiv-cs-lg

ComplexMimic: Human-Scene Interaction Imitation in Complex 3D Environments

arXiv:2607.02034v2 Announce Type: replace Abstract: Physics-based Human-Scene Interaction (HSI) imitation learning is crucial for embodied intelligence as it bridges the gap between kinematic 3D motio

Conditional Diffusion Guided Knowledge Transfer for Multi-Domain Knowledge Graph Completion

arXiv:2607.03154v1 Announce Type: cross Abstract: Multi-domain knowledge graph completion (MKGC) aims to improve missing triple prediction in a target KG by transferring knowledge from other support K

Conservative Subject Invariant EMG-based Gesture Recognition

model-releasesarxiv-cs-lg

arXiv:2607.03783v1 Announce Type: new Abstract: Cross-subject generalization remains a fundamental challenge in surface electromyography (sEMG)-based gesture recognition. Although deep learning method

Contaminated Multi-task Learning with Heterogeneity: Fundamental Limits and Optimal Algorithms

model-releasesarxiv-cs-lg

arXiv:2607.02681v1 Announce Type: cross Abstract: Integrating information across related tasks can improve estimation and prediction in transfer, multi-task, and federated learning, but contamination

Context Tuning for In-Context Optimization

arXiv:2507.04221v3 Announce Type: replace-cross Abstract: We introduce Context Tuning, a simple and effective method to significantly enhance few-shot adaptation of large language models (LLMs) withou

Continuous-Time Gaussian Belief Trees for Motion Planning

model-releasesarxiv-cs-ro

arXiv:2607.02884v1 Announce Type: new Abstract: We address sampling-based motion planning for continuous-time stochastic systems under process and measurement uncertainty, with probabilistic guarantee

CoRE-VLA: Towards Scalable and Robust Vision-Language-Action Modeling via Conditional Routing of Experts

arXiv:2607.03693v1 Announce Type: new Abstract: Vision-language-action (VLA) models have advanced generalist robotic manipulation, yet real-world deployment reveals a fundamental challenge: robots are

safetyarxiv-cs-ro

Correlation-Weighted Multi-Reward Optimization for Compositional Generation

arXiv:2603.18528v2 Announce Type: replace Abstract: Text-to-image models produce images that align well with natural language prompts, but compositional generation has long been a central challenge. M

Criterion-Conditional In-Context Learning: Evaluating Criterion-Shift Adaptation in Vision-Language Models

arXiv:2607.02575v1 Announce Type: cross Abstract: Vision-language models can perform new tasks without parameter updates through in-context learning (ICL), whose core mechanism is utilizing the suppor

CritiqueDriveVLM: From Verifier-Guided Reinforcement Learning to Latent Thought Distillation for Autonomous Driving

arXiv:2607.04179v1 Announce Type: cross Abstract: End-to-end Vision-Language Models (VLMs) show immense potential in autonomous driving. However, standard Supervised Fine-Tuning (SFT) often suffers fr

Applications

Cross-device Collaborative Test-time Adaptation with Zeroth-order Optimization and Model Merging

arXiv:2607.02988v1 Announce Type: new Abstract: Test-time adaptation (TTA) mitigates domain shifts by using incoming test data to update a model on the fly. The majority of TTA methods require resourc

applicationsarxiv-cs-cv

CuBAS: Information Geometric Curvature-Based Adaptive Sampling for Supervised Classification

arXiv:2607.03145v1 Announce Type: cross Abstract: The informativeness of a training set is as consequential as its size, yet most sampling strategies remain agnostic to the intrinsic geometry of the d

CURE: Controllable Unified Image Restoration for Complex Degradations

arXiv:2607.03044v1 Announce Type: new Abstract: The presence of composite degradations poses a significant challenge, since the underlying corruption factors exhibit complex and interdependent interac

researcharxiv-cs-cv

CV-DCLR: Causal-Visual Dynamic Label Refinement for Robust Zero-Shot Learning

arXiv:2607.02601v1 Announce Type: new Abstract: Zero-Shot Learning (ZSL) facilitates knowledge transfer via shared semantic spaces. However, a critical bottleneck in this paradigm is Semantic Entangle

safetyarxiv-cs-cv