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Memory Is Not Always Needed: Characterizing Conditional Memory in Scientific Reasoning

arXiv:2608.23982v1 Announce Type: new Abstract: Scientific reasoning requires language models to retrieve specialized knowledge and incorporate it reliably into multi-step computation. Conditional mem

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MetaRAG: Belief-Action Aligned Policy Optimization for Agentic RAG

DGX agent

arXiv:2608.24214v1 Announce Type: new Abstract: Agentic retrieval-augmented generation (RAG) requires language models to decide when to continue searching and when to answer. Existing RL-based methods

safetyarxiv-cs-ai

26 Aug 2026

MoRF-AST: Calibrated Probabilistic Virtual Sensing for Structural Monitoring under Changing Operating Conditions

arXiv:2608.24531v1 Announce Type: cross Abstract: Probabilistic full-field reconstruction provides uncertainty-aware response evidence for structural reliability assessment, yet inference from sparse

MPIB: A Benchmark for Medical Prompt Injection Attacks and Clinical Safety in LLMs

arXiv:2602.06268v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) systems are increasingly integrated into clinical workflows. However, pr

NeuralParker: A Reinforcement Learning Planner for Irregular Parking Environments

arXiv:2608.24485v1 Announce Type: cross Abstract: Automated parking commonly assumes marked slots and short approach maneuvers. Delivery and service vehicles, however, may need to reach an operator-sp

safetyarxiv-cs-lg

Olapa-MCoT: Enhancing the Chinese Mathematical Reasoning Capability of LLMs

arXiv:2312.17535v2 Announce Type: replace Abstract: In the past two years, the outstanding performance of ChatGPT in multilingual and multitasking has led to large language models (LLMs) attracting wi

Opponent Aware Reinforcement Learning

arXiv:1908.08773v3 Announce Type: replace Abstract: In certain reinforcement learning (RL) scenarios there are adversaries trying to interfere with the underlying reward process for their own benefit.

agentsarxiv-cs-lg

Parason: Revealing Subtask and Trial Parallelism in LLM Reasoning

arXiv:2608.24658v1 Announce Type: new Abstract: Scaling test-time reasoning has substantially improved the problem-solving ability of large language models (LLMs), but standard autoregressive decoding

Place, Slice and Schedule: Hierarchical O-RAN Control of a Tethered mmWave UAV-gNB

arXiv:2608.23824v1 Announce Type: cross Abstract: Unmanned aerial vehicle (UAV)-mounted 5G New Radio base stations (gNBs) can augment terrestrial networks with an on-demand, repositionable Frequency R

RefineRank: Joint Box Refinement and Ranking for Surgical Spatio-Temporal Grounding

arXiv:2608.23928v1 Announce Type: cross Abstract: Surgical spatio-temporal grounding (STG) requires locating, at each video time specified by a procedural question, the object that the question asks a

local-aiarxiv-cs-ai

Semantic Overlays: Mitigating Prompt Injection with Annotations Beyond Tokens and Steering Vectors

arXiv:2608.23873v1 Announce Type: new Abstract: Everything a language model sees is tokens. The serving stack knows what each span is -- user input, tool output, instructions -- but the model must kee

Spatiotemporal Distillation via Recurrent Bottlenecks for Aortic Tracking

arXiv:2608.23879v1 Announce Type: cross Abstract: Cardiac cine-MRI serves as a direct visual indicator of cardiovascular hemodynamics by capturing the continuous wall motion of the aorta. Quantifying

researcharxiv-cs-cv

StateTune: Transforming LLM-Assisted EDA Flow Tuning into a Stateful, Closed-Loop Process

arXiv:2608.23601v1 Announce Type: cross Abstract: EDA flow parameter tuning is critical for quality-of-results~(QoR), yet the parameter space is large, tightly coupled, and full evaluations are prohib

StepGuard: Learning Step-Level Guardrails with Scalable Supervision and Safety-Utility Balancing

arXiv:2608.24777v1 Announce Type: new Abstract: LLM-based agents can interact with external environments through tool invocation, but this capability also introduces security risks such as file modifi

Structured Frequency-Domain Evidence for LLM-Based Time-Series Anomaly Detection

arXiv:2608.24113v1 Announce Type: cross Abstract: Time-series anomalies can appear not only as pointwise deviations but also as changes in recurring temporal structure, such as shifted periodicity or

Taming foundation model with invariance-oriented pre-training for broad-spectrum EEG analysis across signal-level, brain-state, and brain-health tasks

arXiv:2608.24597v1 Announce Type: cross Abstract: Electroencephalography (EEG) is a widely used window into human brain function, but most EEG models remain tied to a one-dataset-one-model supervised

The Shadow Price of Intelligence: Quality Degradation in LLM Inference as a Supply Chain Problem

arXiv:2608.23986v1 Announce Type: cross Abstract: Large language model providers are compute constrained, and their universal response to congestion is to degrade service: route queries to smaller mod

safetyarxiv-cs-ai

UHI-Bench: Benchmarking Dual-Source Urban Heat Island Modeling Across Cities in Diverse Climate Regimes

arXiv:2608.23857v1 Announce Type: new Abstract: Urban heat islands (UHIs) are intensifying under climate change, exacerbating thermal exposure risks. Their two primary observations, land surface tempe

When Can One Neuron Fix Repetition Loops in LLMs?

arXiv:2606.13705v2 Announce Type: replace-cross Abstract: The Gemma 4 instruction-tuned models share a reproducible failure: on long factual enumeration prompts, such as TV episodes, the 88 IAU conste

When Less Is More: An Empirical Study of Minimal Responses in Counseling Dialogues and the Behavior of LLMs

arXiv:2608.24080v1 Announce Type: cross Abstract: In psychological counseling, effective support is not always delivered through long, information-rich responses. Minimal responses, such as backchanne

A Modular Multitask Reasoning Framework Integrating Spatio-temporal Models and LLMs

arXiv:2506.20073v2 Announce Type: replace-cross Abstract: Spatio-temporal data mining plays a pivotal role in informed decision making across diverse domains. However, existing models are often restri

Tutorials

Adaptive Item-based Collaborative Structures via Noise Rescheduling in Diffusion for Generative Recommendation

arXiv:2608.23400v1 Announce Type: cross Abstract: Discrete Diffusion Models (DDMs) have recently been introduced to recommendation systems, modeling user history as a token generation process via iter

tutorialsarxiv-cs-ai

AdaSemSeg: An Adaptive Few-shot Semantic Segmentation of Seismic Facies

arXiv:2501.16760v2 Announce Type: replace Abstract: Automated interpretation of seismic images using deep learning methods is challenging because of the limited availability of training data. Few-shot

researcharxiv-cs-cv

AnaDiffusion: Anatomically CompositionalLatent Diffusion for Controllable 3D Brain MRI Generation

arXiv:2608.23014v1 Announce Type: new Abstract: 3D brain MRI generation has made significant advances in medical imaging, simulation, and controllable anatomical analysis. However, existing generative

local-aiarxiv-cs-cv

Benchmarking Retrieval-Augmented Generation Strategies for Large Language Model-Based Travel Mode Choice Prediction

arXiv:2508.17527v2 Announce Type: replace Abstract: Accurately predicting travel mode choice is essential for effective transportation planning, yet traditional statistical and machine learning models

Beyond Instance Slots: Semantically Rich World Models for Physical Interaction Planning

arXiv:2608.22294v1 Announce Type: new Abstract: World models for physical interaction are typically trained to predict future observations or latent features; however, a planning-oriented model must a

researcharxiv-cs-ro

Beyond Similarity: Heterogeneous Graph Learning for Multi-Objective Food Substitution in Charitable Food Agencies

arXiv:2608.21979v1 Announce Type: new Abstract: Charitable food agencies play an important role in alleviating food insecurity by distributing donated food to people in need. However, they rely on ad

Beyond Two Bytes per Letter: Tokenization Overhead in Cyrillic AI Systems

arXiv:2608.21384v1 Announce Type: cross Abstract: Modern multilingual tokenizers often fragment Ukrainian and other underrepresented Cyrillic-script languages more heavily than English, creating dispa

Beyond Verdicts: A Graph-Based Analysis of Human and LLM Reasoning in Scientific Fact-Checking

arXiv:2608.23047v1 Announce Type: cross Abstract: Misinformation that cites legitimate papers can be especially harmful when it distorts what those studies actually report. While existing automatic fa

BioMed-Agent-RL: A Meta Learning, All You Need for Biomedical Applications

arXiv:2608.21864v1 Announce Type: cross Abstract: The current progress of Clinical Vision Large Language Models (C-VLLMs) has substantially improved digital diagnostics, still these frameworks often e

Budget-Constrained Embodied Perception: Four Resource Walls and a Pre-Registered Evaluation of Access-Structured Perception on Open Models at less than 31B

arXiv:2608.22975v1 Announce Type: new Abstract: Embodied multimodal agents must answer from growing observation streams under a fixed per-decision token budget. We formalize this constraint through fo

Tutorials

CAI-DLLM: Convergence Aware Inference for Diffusion Language Models

arXiv:2608.22646v1 Announce Type: new Abstract: Diffusion language models can generate many tokens in parallel, but they still require repeated denoising steps during inference. This makes generation

tutorialsarxiv-cs-ai

CausalCache: Conditional High-Fidelity Restoration for Long-Horizon GUI Agents

arXiv:2608.22577v1 Announce Type: new Abstract: Long-horizon GUI agents can retain a complete interaction trace cheaply as textual action records, but expose only a few past events to the policy in hi

Change Detection in Probability Flow ODE: Online Testing in Diffusion Latent Spaces

arXiv:2608.22807v1 Announce Type: new Abstract: A rapidly growing range of sequential data tasks, such as identifying trend reversals in financial markets, auto-segmenting video and audio recordings,

researcharxiv-cs-lg

Channel-Token Attention for Reliable Dynamic Spectrum Access under Bursty Primary-User Traffic

arXiv:2608.22992v1 Announce Type: cross Abstract: Dynamic spectrum access must coordinate secondary users under bursty primary-user activity while preserving packet reliability and delay. We present T

safetyarxiv-cs-lg

CiUNet: A Hybrid Swin-CNN UNet for Medical Image Segmentation

arXiv:2608.22281v1 Announce Type: cross Abstract: Medical image segmentation requires high accuracy and robustness, yet practical commercial deployment also demands privacy preservation and computatio

local-aiarxiv-cs-cv

Cross-lingual Biography Enrichment via Claim Extraction and Alignment

arXiv:2608.23390v1 Announce Type: cross Abstract: English Wikipedia is often treated as the default encyclopedic source, yet non-English Wikipedia editions can contain richer locally grounded informat

Do Not Copy/Paste: Soft Barriers for Copying in AI-Assisted Programming

arXiv:2608.22638v1 Announce Type: cross Abstract: Copying a function from a chat window into an editor takes less than a second. For many uses of AI coding tools, that speed is the point; in settings

safetyarxiv-cs-ai

DRBD-Mamba for Robust and Efficient Brain Tumor Segmentation with Analytical Insights

arXiv:2510.14383v4 Announce Type: replace Abstract: Accurate brain tumor segmentation is significant for clinical diagnosis and treatment but remains challenging due to tumor heterogeneity. Mamba-base

local-aiarxiv-cs-cv

Dual-Scale State-Space Modeling with Speaker-Wise Dynamic CRF for Speech Emotion Recognition in Conversation

arXiv:2608.22399v1 Announce Type: new Abstract: Conversational speech emotion recognition must reconcile acoustic evidence across temporal scales with two interaction processes: cross-speaker contextu

local-aiarxiv-cs-lg

Dynamic Cogeneration of Bug Reproduction Test in Agentic Program Repair

arXiv:2601.19066v3 Announce Type: replace-cross Abstract: Bug Reproduction Tests (BRTs) have been used in many Automated Program Repair (APR) systems, primarily for validating fixes and aiding fix gen

agentsarxiv-cs-ai

Tutorials

EMPIRE: Explicit Manipulation Planning as a Learnable Intermediate Representation for Egocentric Hand-Motion Forecasting

arXiv:2608.22449v1 Announce Type: cross Abstract: Forecasting dexterous hand motions from egocentric observations is fundamental to intelligent interactive systems. Existing VLM-based methods typicall

tutorialsarxiv-cs-ai

EndoNav: Semantic-to-Geometric Grounding for Language-Guided Robotic Endoscopic Examination

arXiv:2608.22093v1 Announce Type: new Abstract: Minimally invasive procedures performed within confined anatomical spaces depend on continuous endoscopic visualization. Current robotic endoscope syste

agentsarxiv-cs-ro

Environmental Injection Attacks against GUI Agents in Realistic Dynamic Environments

arXiv:2509.11250v3 Announce Type: replace-cross Abstract: Graphical User Interface (GUI) agents are increasingly deployed to interact with online web services, yet their exposure to open-world content

agentsarxiv-cs-cv

Evaluation Awareness in Language Models: Representation, Verbalization, and Control

arXiv:2608.21766v1 Announce Type: cross Abstract: Both capability and safety benchmarks rest upon the assumption that the behavior of language models undergoing a test is informative about their behav

safetyarxiv-cs-ai

EvoWiki: Incremental State Overwriting and Traceable Question Answering for Cross-Meeting Knowledge Evolution

model-releasesarxiv-cs-cl

arXiv:2608.23265v1 Announce Type: new Abstract: In long-term collaboration spanning multiple meetings, factual states such as decisions and risks are continually revised, overturned, and replaced. Exi

Expert-level vision-language foundation model for real-world radiology and comprehensive evaluation

model-releasesarxiv-cs-cv

arXiv:2409.16183v2 Announce Type: replace Abstract: Radiology is a vital and complex component of modern clinical workflow and covers many tasks. Recently, vision-language (VL) foundation models in me

ExploreAI: Agentic Exploration Knowledge Bases for Reproducible Observable-Regression Testing of Black-Box VR and 3D Applications

arXiv:2608.21628v1 Announce Type: cross Abstract: Black-box VR and 3D applications are difficult to regression test because observable failures depend on where a tester moves, what objects are visible

safetyarxiv-cs-ro