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SCAR: Semantic Continuity-Aware Retrieval for Efficient Context Expansion in RAG

arXiv:2606.16661v2 Announce Type: replace-cross Abstract: Fixed-length chunking in Retrieval-Augmented Generation (RAG) often leads to boundary fragmentation, where critical evidence is split across s

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SDoH-Aware Narrative Anchoring Bias in Medical LLMs for Trustworthy Clinical Decision Support

DGX agent

arXiv:2608.22802v1 Announce Type: cross Abstract: Medical large language models are often judged by how many clinical questions they answer correctly. That view is useful, but it misses a practical ri

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25 Aug 2026

SecOPD: Mitigating Adaptive Prompt Injections by On-Policy Distillation

arXiv:2608.21500v1 Announce Type: cross Abstract: Prompt injection is listed as the #1 threat to AI agents. When an agent accesses external data from websites, files, or emails, an attacker may inject

Self-Supervised Graph Representation Learning for In-The-Wild Wearable and Smartphone based Emotion Recognition

arXiv:2608.22387v1 Announce Type: cross Abstract: Wearable and smartphone-based emotion recognition (WER) remains a challenging setting in affective computing, due to the notorious difficulty and bias

Semiparametric Double Reinforcement Learning with Applications to Long-Term Causal Inference

arXiv:2501.06926v5 Announce Type: replace-cross Abstract: Double reinforcement learning (DRL) provides efficient off-policy inference for policy values in nonparametric Markov decision processes (MDPs

Shaping the Evolutionary Dynamics of Robot Morphology via Adaptive Control Learning

arXiv:2608.23100v1 Announce Type: cross Abstract: Robot co-design via bi-level optimization couples within-lifetime controller learning for fitness evaluation with cross-generational morphological evo

Simplified Cross-Modal Calibration for Heterogeneous Event-RGB Stereo Systems

arXiv:2608.22965v1 Announce Type: new Abstract: Accurate extrinsic calibration between event-based and frame-based cameras remains a practical bottleneck for heterogeneous stereo systems. Existing app

SketchFlow: Zero-Shot Vector Sketch Generation via GMM Prior Flow in CLIP Latent Space

arXiv:2608.21659v1 Announce Type: new Abstract: Vector sketches remain one of the most concise and immediate mediums for abstract human expression. However, generating high-quality vector strokes that

Sparse Additive Off-Policy Evaluation for Reinforcement Learning with Potentially Limited Number of Trajectories

arXiv:2608.22595v1 Announce Type: cross Abstract: We develop a new framework for flexible, nonlinear, and interpretable off-policy evaluation for infinite-horizon reinforcement learning. To handle lar

SRPO: Self-Reflective Policy Optimization for Long-Horizon Reasoning

arXiv:2608.23493v1 Announce Type: new Abstract: Self-reflection is a powerful mechanism for credit assignment in human learning, converting sparse outcome feedback into actionable guidance. However, i

SSE-Bio: A Structured Self-Evolving Agent with Agentic Retrieval Policy for Multi-Hop Biomedical Reasoning

arXiv:2608.22132v1 Announce Type: cross Abstract: Biomedical multi-hop question answering (QA) requires models to connect evidence across intermediate entities such as diseases, drugs, proteins, and p

STA-VPT: SpatioTemporally Aligned Visual Prompt Tuning

arXiv:2312.10376v2 Announce Type: replace Abstract: Typical methods for visual prompt tuning follow the sequential modeling paradigm originating from NLP, learning a sequence of unordered parameterize

SVD-Based Typicality Maps for Out-of-Distribution Detection in Vision Transformers

arXiv:2608.23499v1 Announce Type: new Abstract: We present a method for analyzing the internal representations of Vision Transformers (ViTs) exploiting the geometry of their learned parameters. Each a

Syntax-Guided Diffusion Language Models with User-Integrated Personalization

arXiv:2510.01028v2 Announce Type: replace Abstract: Large language models have made revolutionary progress in generating human-like text, yet their outputs often tend to be generic, exhibiting insuffi

TailSieve: Partial-Rollout-Guided Tail Routing for LLM Rollouts

arXiv:2608.22788v1 Announce Type: new Abstract: Large-scale rollouts have become a core component of modern LLM systems, spanning reinforcement learning (RL) post-training, on-policy distillation (OPD

The Plan, Not the Decoder: Diagnosing and Repairing Compositional Failure in Reasoning-Augmented Text-to-Image Generation

arXiv:2608.21713v1 Announce Type: cross Abstract: Reasoning-augmented text-to-image models such as GoT-R1 emit an explicit textual plan - object names, attributes, and bounding boxes - before generati

The Variance of Thought: Policy Variance, Critical Forks, and Local Credit Assignment

arXiv:2608.22467v1 Announce Type: new Abstract: Long-horizon language-model tasks --- multi-step reasoning and tool-using agents alike --- are limited by credit assignment. We analyze it through the p

Think Only When Needed: Prompt-Authority Control for Selective Slow-Path Intervention in Vision-Language-Action Manipulation

arXiv:2608.23224v1 Announce Type: cross Abstract: Retrieval can efficiently and effectively augment a frozen vision--language--action (VLA) policy without retraining, yet retrieved text becomes a cont

Thinking at the Right Size: Amortized Distillation Across Post-Trained LLMs

arXiv:2608.22854v1 Announce Type: new Abstract: Practical deployment of large language models (LLMs) requires families of post-trained variants---instruction-tuned, reasoning-tuned, and chat-style mod

Training Needs Trustworthy Worlds: Verified Synthetic Web Environments for Agent Learning

arXiv:2608.21898v1 Announce Type: new Abstract: Web agents promise to automate complex digital workflows, but their training remains limited by synthetic environments that look plausible while hiding

UniMem: Unifying Multimodal Memory and Control for Vision-Language-Action Models

arXiv:2608.22869v1 Announce Type: cross Abstract: While Vision-Language-Action (VLA) models have leveraged internet-scale pretraining and task-focused finetuning to achieve strong performance on long-

Variance Driven Exploration: A Provable and Efficient Methodology for Pure Exploration in Highly Stochastic Environments

arXiv:2608.21995v1 Announce Type: cross Abstract: We propose Variance Driven Exploration (VarDE), a principled approach for pure exploration in highly stochastic environments, where the exploration pr

VIG: Visual Information Gain as a Reward Signal for Multimodal Chain-of-Thought Compression

arXiv:2608.21883v1 Announce Type: new Abstract: Multimodal large reasoning models often rely on long Chain-of-Thought (CoT) traces in which a substantial fraction of tokens, such as repeated visual de

VinciCoder: Unifying Multimodal Code Generation via Coarse-to-fine Visual Reinforcement Learning

arXiv:2511.00391v3 Announce Type: replace Abstract: While recent specialized multimodal code generation models excel in tasks like chart-to-code generation, their reliance on single-task training limi

ViSMoE: Visual-Aware Sparse Mixture-of-Experts for Embodied Referring Expression Grounding

arXiv:2608.21878v1 Announce Type: new Abstract: Embodied Referring Expression Grounding is the task of enabling an agent to navigate in real environments and to localize a remote object based on natur

VISTA: Test-Time Compositional Alignment for Visual Autoregressive Generation

arXiv:2608.22521v1 Announce Type: new Abstract: Visual autoregressive (VAR) models have emerged as a fast, high-quality alternative to diffusion for text-to-image generation, but like diffusion models

ViTexSZ: Heterogeneous Vision-Text Knowledge Distillation for EEG Seizure Detection

arXiv:2608.21445v1 Announce Type: new Abstract: Automated seizure detection from electroencephalography (EEG) is essential for continuous neurological monitoring, particularly for subclinical epilepti

Weakly supervised concept Bottleneck Learning for Robust Two stage Object centric visual reasoning

arXiv:2608.22584v1 Announce Type: new Abstract: Two-stage neuro-symbolic architectures provide an elegant paradigm for visual problem solving by cleanly separating connectionist perception of predefin

What Process Evaluation of Coding Agents Actually Measures: Action, Task, and Step Are Three Different Levels

arXiv:2608.22960v1 Announce Type: new Abstract: Coding agents are increasingly evaluated not only by whether they solve a task, but also by how they execute it. However, existing process-level evaluat

When a neural surrogate cannot accelerate a solver: runtime share, closed-loop drift, and the economics of uncertainty gating in a stiff coupled simulation

arXiv:2608.23075v1 Announce Type: cross Abstract: Learned surrogates for expensive inner solver blocks are a widely pursued route to faster multiphysics simulation. We report a controlled, end-to-end

When the Edit Changes the Patient: Measuring Identity Preservation in Counterfactual Retinal Images

arXiv:2608.23024v1 Announce Type: new Abstract: Counterfactual medical image generation aims to modify an existing image to reflect a hypothetical scenario in which certain characteristics of the imag

WSJ: 'Anthropic more than doubled its revenue to 11.6 billion in the second quarter. To put its more than 30 trillion vision in context, t…

WSJ: 'Anthropic more than doubled its revenue to 11.6 billion in the second quarter. To put its more than 30 trillion vision in context, the 191 technology companies in the S&P 1500 brought in 2.4 tri

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Your AI, On a Dial: Controlling Investment Bias in LLMs with a Single Neuron

arXiv:2608.22852v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in investment decision-making, yet prior work shows that they exhibit systematic, model-specific inve

A Deep Reinforcement Learning Framework for Closed-loop Guidance of Fish Schools via Virtual Agents

arXiv:2603.28200v2 Announce Type: replace-cross Abstract: Guiding collective motion in biological groups is a fundamental challenge in understanding social interaction rules. In this study, we propose

Advantage-level Aggregation Reinforcement Learning for X-point Target Magnetic Configuration Control in an EXL-50U Experiment-Calibrated Simulation Environment

arXiv:2608.20834v1 Announce Type: cross Abstract: Managing divertor heat loads is a central challenge for compact, high-power tokamaks. To increase local flux expansion and decouple the dissipation vo

AEGIS: Preventing Cross-Domain Resource Abuse in MCP

arXiv:2608.20481v1 Announce Type: cross Abstract: The Model Context Protocol (MCP) is an open source JSON-RPC protocol that standardizes how large language models (LLMs) interact with external systems

AI-driven Prices for Externalities and Sustainability in Production Markets

arXiv:2106.06060v4 Announce Type: replace-cross Abstract: Traditional competitive markets do not account for negative externalities; indirect costs that some participants impose on others, such as the

AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning

arXiv:2508.14313v4 Announce Type: replace-cross Abstract: Test-time scaling strategies for Large Language Models predominantly rely on either reinforcement learning with sparse outcome rewards or sear

Anchoring Instruction Outside Mask: Exact Reference Caching for Efficient In-Context Diffusion Transformers

arXiv:2608.21229v1 Announce Type: new Abstract: Omnimodal generation is central to a wide range of content creation and editing applications. In-context conditioning is essential to this paradigm. It

Ansari: A Retrieval-Grounded Islamic AI Assistant -- Architecture, Deployment, and Lessons from 140,000 Conversations

arXiv:2608.20390v1 Announce Type: cross Abstract: General-purpose large language models (LLMs) are increasingly used to answer religious questions, but for Islamic content they carry two serious risks

AT-ViT: Area-Targeted Multi-View Vision Transformer with Cross-Attention and Multi-Scale Patching for Plant Trait Recognition in Herbarium Images

arXiv:2608.21067v1 Announce Type: cross Abstract: Automated plant traits recognition from herbarium images is essential for plant sciences, yet remains challenging because background elements (e.g., t

AUSO: Action-Level Unified Skill Optimization from Internalization to Utilization

arXiv:2608.21292v1 Announce Type: new Abstract: Skills play different roles as an agent's policy evolves: they should first provide learnable knowledge, then support capability formation, and finally

BIPPO: Budget-Aware Independent PPO for Energy-Efficient Federated Learning Services

arXiv:2511.08142v2 Announce Type: replace Abstract: Federated Learning (FL) is a promising machine learning solution in large-scale IoT systems, guaranteeing load distribution and privacy. However, FL

Bridging Language and Spherical Space: Object-Centric Control for Text-to-Panorama Generation

arXiv:2608.20691v1 Announce Type: new Abstract: Panoramic image generation is increasingly important for immersive applications such as virtual reality, augmented reality, and 3D content creation. Unl

Can We Trust AI Agents? A Case Study of an LLM-Based Multi-Agent System for Ethical AI

arXiv:2411.08881v3 Announce Type: replace-cross Abstract: AI-based systems, including Large Language Models (LLMs), impact millions by supporting diverse tasks but face issues like misinformation, bia

CAS: Conformalized Agentic Search via Adaptive Retrieval and Policy Weighting

arXiv:2608.20771v1 Announce Type: new Abstract: Search Agents face a severe reliability crisis during reinforcement learning (RL) fine-tuning. Heuristic Top-K retrieval often causes critical evidence

COMET: Contrastive Motion-Enhanced Temporal Reasoning for Video Multimodal Large Language Models

arXiv:2608.21030v1 Announce Type: cross Abstract: Video multimodal large language models have advanced significantly, yet fine-grained motion-temporal understanding remains fragile. The core bottlenec

Continuous-Time Quantum Walks based Graph Neural Network

arXiv:2608.20738v1 Announce Type: new Abstract: Graph Neural Networks (GNNs) are widely used on graph-structured data, but most suffer from two key weaknesses. First, message passing behaves as a low-