Search: “context”

Linearized 2-Simplicial Attention

arXiv:2608.09307v1 Announce Type: new Abstract: We present a linearized form of 2-simplicial attention by rewriting the trilinear score as an inner product between a composite query and a key, so that

LineGraph2Road: Structural Graph Reasoning on Line Graphs for Road Network Extraction

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arXiv:2602.23290v2 Announce Type: replace Abstract: Extracting routable road networks from satellite imagery requires accurate topology recovery beyond pixel-level segmentation. Recent methods decompo

applicationsarxiv-cs-cv

11 Aug 2026

Linguistically-Aligned and Visually-Grounded Preference Optimization for Clinically-Augmented Medical Report Generation

arXiv:2608.08494v1 Announce Type: new Abstract: Despite significant advances in Medical Report Generation (MRG), the reliability remains constrained by the prevalence of factual errors. While Direct P

safetyarxiv-cs-cv

Listen, See and Track: Spatio-Temporal Audio-Visual Sound Event Reasoning for Omni-Modal Language Models

arXiv:2608.09435v1 Announce Type: new Abstract: Understanding dynamic sound sources requires jointly determining what produces a sound, where the source is located, and how it moves over time. Yet exi

LLM Reasoning for Subjective Tasks: Failure Modes, Mitigation, and Dynamic Reasoning Routing

arXiv:2608.08889v1 Announce Type: new Abstract: Recommendation systems thrive on personalization, where ''correctness'' is rarely a binary truth but a matter of subjective human preference. As Large L

Locating Failure in Multi-Page Visually Rich Document Understanding: An Empirical Attribution

arXiv:2608.07943v1 Announce Type: new Abstract: Multi-page visually-rich document understanding (MP-VRDU) requires managing evidence that is sparse, spread across pages, and often exceeds a model's co

Local Ai

Macaron-V1: Towards Open Continual Learning with Self-Improvement and Mixture-of-LoRA

arXiv:2608.09819v1 Announce Type: cross Abstract: Macaron-V1 is an open agent-model family for experiential intelligence: learning from experience in real environments and continuing to learn after de

local-aiarxiv-cs-cl

Math-Vision Diagrams: A Comprehensive Benchmark for Evaluating LLM Mathematical Diagram Generation Capabilities

model-releasesarxiv-cs-lg

arXiv:2608.08964v1 Announce Type: new Abstract: The generation of mathematically precise diagrams from tex- tual prompts has emerged as a critical yet underexplored capability of Large Language Models

Matrix-free Neural Preconditioner for the Dirac Operator in Lattice Gauge Theory

model-releasesarxiv-cs-lg

arXiv:2509.10378v2 Announce Type: replace-cross Abstract: Linear systems arise in generating samples and in calculating observables in lattice quantum chromodynamics~(QCD). Solving the Hermitian posit

MixFormer: Linear Transformer with Mixture of Memory Experts

arXiv:2608.09468v1 Announce Type: cross Abstract: State Space Models (SSMs), as a mainstream research direction of linear Transformers, aim to achieve higher efficiency than standard Transformers in l

Model the Edit, Not the Image: Visual Autoregressive Editing from a Source-Centric Perspective

arXiv:2608.09057v1 Announce Type: new Abstract: Next-scale visual autoregressive models (VARs) have emerged as a powerful generative paradigm, producing high-quality images through efficient coarse-to

safetyarxiv-cs-cv

MPISuperRes-PnP: A Super-Resolution Zero-Shot Plug-and-Play Reconstruction Algorithm for Magnetic Particle Imaging

model-releasesarxiv-cs-cv

arXiv:2608.09672v1 Announce Type: new Abstract: Magnetic Particle Imaging (MPI) is an emerging medical imaging modality. MPI is based on the non-linear response of magnetic nanoparticles to an applied

Multi-Task Consistency-based Detection of Adversarial Attacks

arXiv:2608.07750v1 Announce Type: cross Abstract: Deep Neural Networks (DNNs) have found successful deployment in numerous vision perception systems. However, their susceptibility to adversarial attac

agentsarxiv-cs-ai

Multimodal Skin Lesion Classification with Swin Transformer and Clinical Metadata Fusion

arXiv:2608.07574v1 Announce Type: new Abstract: Skin lesion classification plays an important role in supporting the early diagnosis of skin cancer. However, automated analysis remains challenging due

researcharxiv-cs-cv

Neurosymbolic Discovery of Algebraic Graph Constructions

arXiv:2608.08118v1 Announce Type: new Abstract: There are several methods for searching for graphs with prescribed properties, such as SAT solvers and specialized generators. These methods return the

On the Effect of Sampling Diversity in Scaling LLM Inference

arXiv:2502.11027v5 Announce Type: replace Abstract: Large language model (LLM) scaling inference is key to unlocking greater performance, and leveraging diversity has proven an effective way to enhanc

researcharxiv-cs-lg

OnEvoMemory: Evolving Memory through Online Robot Rollouts for Pretrained Robot Policies

arXiv:2608.08749v1 Announce Type: new Abstract: Long-horizon robot manipulation requires policies to track completed subtasks and critical interaction events. However, existing memory mechanisms heavi

safetyarxiv-cs-ro

OpenLoopEvolve: A Verifiable Self-Evolution Framework for Loop Policies in Long-Horizon Complex Tasks

arXiv:2608.09380v1 Announce Type: new Abstract: Long-horizon complex tasks require agents to repeatedly observe states, formulate plans, invoke tools, verify results, and recover from failures in cont

PARAGraph: Pathology-Anatomy-Aware Hierarchical Graph for Diabetic Retinopathy Grading

arXiv:2608.08368v1 Announce Type: new Abstract: Diabetic retinopathy (DR) remains a leading cause of vision loss among working-age adults worldwide, making reliable severity grading clinically importa

researcharxiv-cs-cv

PAST: Privileged Adaptation from Complete Student Trajectories for On-Policy Self-Distillation

arXiv:2608.08726v1 Announce Type: cross Abstract: On-policy self-distillation (OPSD) uses a privileged teacher to supervise a reasoning model on prefixes sampled from its own rollouts. Yet each rollou

PE-Mamba: Bidirectional Selective Layer Aggregation for AI-Generated Image Detection

arXiv:2608.07999v1 Announce Type: new Abstract: AI-generated image (AIGI) detection has become increasingly challenging due to the rapid advancement of generative models and the diminishing gap betwee

researcharxiv-cs-cv

Perception Before Supervision: Self-Contained Visual Distillation from Counterfactual Blind Spots

arXiv:2608.09931v1 Announce Type: new Abstract: Self-improvement for multimodal large language models (MLLMs) is typically driven by reward-based methods that provide only coarse scalar feedback. Dist

safetyarxiv-cs-cv

Persistent Semantic Entities in Tool-Augmented LLM Systems

arXiv:2608.07952v1 Announce Type: cross Abstract: Tool-augmented LLM agents can harbor implicit state that persists across sessions, activates through events, and propagates across agent boundaries---

Privileged Likelihood Is Not Automatically Value: Three Checks for Token Credit in On-Policy Self-Distillation

arXiv:2608.09263v1 Announce Type: new Abstract: Outcome verifiers score completed reasoning traces but do not assign credit to intermediate tokens. Privileged self-distillation attempts to fill this g

Prompt engineering does not universally improve Large Language Model performance across clinical decision-making tasks

arXiv:2512.22966v2 Announce Type: replace Abstract: Large Language Models (LLMs) have demonstrated promise in medical knowledge assessments, yet their practical utility in real-world clinical decision

Protecting patient privacy in clinical foundation models: Technical and legal perspectives

arXiv:2608.07705v1 Announce Type: new Abstract: Clinical foundation models trained on large-scale patient data are increasingly used for decision support, screening, and public health. As deployment e

applicationsarxiv-cs-ai

Real-Time Climate Risk Assessment for Supply Chain Resilience: A Data-Driven Nowcasting Framework for Colombian Agriculture

arXiv:2608.09846v1 Announce Type: new Abstract: This paper presents a methodological framework for real-time climate risk assessment using data-driven nowcasting techniques to enhance supply chain res

applicationsarxiv-cs-lg

REFRAMED: Towards Realistic Audio Description Generation for Movies

arXiv:2608.09765v1 Announce Type: new Abstract: Audio Description (AD) is a verbal narration of key visual content in videos, enabling access for visually impaired audiences. Unlike standard video cap

Regret, equilibrium, and learning in games: A guided tour

arXiv:2608.09389v1 Announce Type: cross Abstract: This note aims to serve as an entry point to the literature on learning in games, a topic with significant theoretical appeal and a wide range of appl

agentsarxiv-cs-lg

Renormalising Generative Models for Active Inference: Foundations, Derivations, and Verification

arXiv:2608.09512v1 Announce Type: new Abstract: Active inference offers a unified framework for perception, learning, and action, but scaling discrete active-inference models to rich spatial and tempo

Rethinking 3D Segmentation from Individual LiDAR Scans: Incidence-Aware Sampling on the SIP Benchmark

model-releasesarxiv-cs-cv

arXiv:2608.07757v1 Announce Type: new Abstract: 3D scene understanding is increasingly important in construction, yet most methods are developed on curated datasets that do not fully reflect real site

REVEAL: A Rubric-Guided Agent for Explicit Evidence Sufficiency Verificationin Long-Video Question Answering

arXiv:2608.08612v1 Announce Type: cross Abstract: Recently, retrieval-augmented and memory-augmented methods have emerged as two promising paradigms for long-video question answering. However, existin

agentsarxiv-cs-ai

SAIN: Structure-Aware Interactive Navigation with Active Dialogue Grounding for Mobile Robot

model-releasesarxiv-cs-ro

arXiv:2608.09196v1 Announce Type: new Abstract: Most existing vision-language navigation tasks assume that instructions are complete and unambiguous. However, real-world robots often encounter natural

Scaling Audio Models Efficiently: A Joint Study of Compute Constraints and Optimization Behavior

arXiv:2606.22790v2 Announce Type: replace-cross Abstract: In this paper, we investigate the tradeoffs between compute allocation and model performance for two speech processing tasks: Automatic Speech

SCOUT: Self-Checking and Recovery-Aware Tool-Thought Agents for Ultra-Long Egocentric Video Reasoning

arXiv:2608.07959v1 Announce Type: new Abstract: Ultra-long egocentric video understanding requires reasoning over temporally sparse evidence distributed across hours or days, challenging current multi

SiriusDeliver: Automating Data Warehouse Delivery at Tencent

arXiv:2608.09185v1 Announce Type: cross Abstract: Enterprise data warehouses (DWs) support business-critical analytics, but warehouse task delivery remains a complicated production process involving c

agentsarxiv-cs-ai

Sparks of Cooperative Reasoning: LLMs as Strategic Hanabi Agents

arXiv:2601.18077v3 Announce Type: replace Abstract: Cooperative reasoning under incomplete information remains challenging for both humans and multi-agent systems. The card game Hanabi embodies this c

Sparse Attention to Emotion: Efficient Facial Emotion Recognition via Token Reduction

arXiv:2608.08873v1 Announce Type: new Abstract: Facial Emotion Recognition (FER) is an important task that has significant implications across various fields such as biometrics, health, and human-comp

applicationsarxiv-cs-cv

Local Ai

SportsGrounder: Proposal-Aided Interleaved Grounding for Dense Sports Video Reasoning

arXiv:2608.07932v1 Announce Type: new Abstract: Sports video analysis is crucial for athletic analytics and broadcasting enhancement. Dense sports video reasoning, however, demands a fine-grained unde

local-aiarxiv-cs-cv

SuperLocalMemory 4.0: The Governed Memory Operating System for AI Agents

arXiv:2608.08253v1 Announce Type: new Abstract: AI agents are becoming shared infrastructure, yet durable memory is commonly assembled from separate retrieval, governance, and operational components.

TCS-BENCH: Benchmarking State-of-the-Art Generative AI Theoretical Computer Science Research Ability

arXiv:2608.09538v1 Announce Type: cross Abstract: We introduce TCS-Bench, a benchmark for evaluating Large Language Models (LLMs) on research-level Theoretical Computer Science (TCS) proof generation.

Tevatron-Elastic: A Unified Abstraction for Training Elastic Retrievers and Rerankers

arXiv:2608.08809v1 Announce Type: new Abstract: A single model scale challenges the flexibility of a production retrieval system: some settings need it faster, others need a smaller index, and the rig

The Anatomy of a Prompt Injection: A Component Model for Structured Analysis

arXiv:2608.07808v1 Announce Type: cross Abstract: Four years after prompt injection was first identified in 2022, attacks are still predominantly documented as verbatim strings rather than structured

The Scaffolding Matters More Than the Interface: A Controlled Comparison of MCP and CLI Tool Use Across Seven Agent Scaffoldings, Five Language Models, and One Software Task

arXiv:2608.08654v1 Announce Type: new Abstract: How much an AI coding agent costs to run can depend more on the agent scaffolding that drives it than on the interface through which it reaches its tool

The Transparency Trap: How AI Disclaimers Create Overconfidence in High-Stakes Decisions

arXiv:2608.07493v1 Announce Type: cross Abstract: Current AI disclaimers often fail to function as intended due to warning habituation and a transparency paradox. As AI-generated information becomes p

safetyarxiv-cs-cl

Time Present and Time Past: Benchmarking Large Language Models on Temporally Evolving Document Understanding

arXiv:2608.08512v1 Announce Type: new Abstract: Evolving documents, such as laws, tax codes, and software documentation, are amended, replaced, and sometimes reverted over time, so a question has diff

TongGuOCR: A Layout-Aware and Token-Augmented OCR Framework for Chinese Historical Documents

arXiv:2608.07917v1 Announce Type: new Abstract: Chinese historical documents preserve valuable cultural heritage, but many collections remain accessible only as scanned page images, preventing full-te

Toward Metacognitive One-Shot Indirect Prompt Injection: Strategy Abstraction Via Outcome-Conditioned Reflection

arXiv:2608.08795v1 Announce Type: cross Abstract: Tool-using large language model (LLM) agents are vulnerable to indirect prompt injection (IPI), in which malicious instructions embedded in external o