Search: “framework”

Dynamic Gated Cross-Modal Fusion with Sarcastic-aware Contrastive Regularization for Multimodal Sarcasm Detection

arXiv:2608.19942v1 Announce Type: new Abstract: Multimodal sarcasm detection aims to identify sarcastic intent from multimodal content, where inconsistencies between literal meaning and contextual cue

safetyarxiv-cs-cl

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Electronic Navigational Chart Change Classification

DGX agent

arXiv:2608.20218v1 Announce Type: new Abstract: Electronic Navigational Charts (ENCs) are geospatial vector datasets used in maritime navigation systems that represent hydrographic and navigational in

safetyarxiv-cs-ai

21 Aug 2026

Enforcing LLM Safety through DMD-based Classification of Prompt-Response Embedding Dynamics

arXiv:2608.19579v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed in high-stakes applications, yet their tendency to generate toxic, harmful, or policy-violating c

Flow Matching-Based PET Image Reconstruction

arXiv:2608.20112v1 Announce Type: cross Abstract: Generative models have shown strong potential for positron emission tomography (PET) image reconstruction. Although diffusion model-based reconstructi

safetyarxiv-cs-cv

From Noise to Signal: Improving Security Log Anomaly Detection Using LLMs with Endpoint-Specific Logs

model-releasesarxiv-cs-lg

arXiv:2608.19938v1 Announce Type: cross Abstract: Existing approaches to anomalous behaviour log detection, such as Wazuh rely primarily on predefined detection rules, while statistical anomaly detect

GRACE: Grounded Reasoning via Adapter Composition and Evidence-Aware Calibration for Educational Visual Question Answering

model-releasesarxiv-cs-cv

arXiv:2608.19355v1 Announce Type: cross Abstract: Educational visual question answering, or VQA, requires models to solve curriculum-oriented multiple-choice questions using both language and visual e

Hear2Act: Benchmarking When Prosody Should Change What an Assistant Does

arXiv:2608.19515v1 Announce Type: new Abstract: Prosodic cues can convey task-relevant information that alters the trajectory and outcome of a task-oriented dialogue, even when the words themselves re

researcharxiv-cs-cl

Heteroscedastic Neural Surrogate Modeling for Robust and Rapid Bayesian Inference in Fusion Plasma Diagnostics

model-releasesarxiv-cs-lg

arXiv:2608.19377v1 Announce Type: cross Abstract: Bayesian inference via Markov Chain Monte Carlo (MCMC) provides effective parameter estimation, but its real-time application in complex physical syst

Kahler landscapes for complex neural network descents and guarantees including a search and destroy of the Calabi-Yau manifold

model-releasesarxiv-cs-lg

arXiv:2608.19584v1 Announce Type: new Abstract: We study landscapes for complex-parameterized networks. Our approach is motivated with an information-theoretic manifold perspective of the parameter an

Learning how to Forget: Fine-tuning for Long-Context Sparse Attention

arXiv:2608.19920v1 Announce Type: new Abstract: A lot of prior work addressed key-value (KV) cache selection and compression by sparse attention to enable long-context inference for transformer langua

safetyarxiv-cs-cl

Learning to Beat: Phenotype-Guided Latent Flow with Regional Motion Priors for Biventricular Motion Synthesis

arXiv:2608.19738v1 Announce Type: cross Abstract: Full-cycle biventricular geometry is essential for characterizing cardiac function. However, dense and temporally consistent 3D+t biventricular meshes

Learning When to Think: Adaptive Reasoning for Test-Time Compute Allocation

arXiv:2608.20256v1 Announce Type: new Abstract: Reasoning language models trained with reinforcement learning typically operate under a fixed token budget rather than an explicitly adaptive one, which

LLMs as Acquisition Policies for Finite-Pool Materials Optimization: A Controlled Study

arXiv:2608.19790v1 Announce Type: new Abstract: Discovering materials with desirable properties often requires searching large candidate spaces while experimental or computational evaluations remain c

researcharxiv-cs-ai

MemTrapBench: Benchmarking Cognitive Traps in LLM Memory Use

arXiv:2608.20202v1 Announce Type: new Abstract: Memory has become a key component of large language models, enabling them to retain information and learn from long-term interactions. However, existing

Model-Less Feedback Control of Space-based Continuum Manipulators using Backbone Tension Optimization

model-releasesarxiv-cs-ro

arXiv:2512.06754v2 Announce Type: replace Abstract: Continuum manipulators offer intrinsic dexterity and safe geometric compliance for navigation within confined and obstacle-rich environments. Howeve

Multi-Method Causal Evidence Synthesis: Ranking Candidate Drivers by Convergent Cross-Method Evidence from Observational Data

arXiv:2608.20187v1 Announce Type: cross Abstract: Practitioners inferring causality from observational data usually rely on a single method and treat its output as causal truth. Recent tools select an

ReCache: Efficient KV Cache Reuse and Compression for Tool-Augmented LLM Agents

model-releasesarxiv-cs-cl

arXiv:2608.19662v1 Announce Type: new Abstract: Agentic language models repeatedly encode tool and skill schemas that recur across requests in different combinations and orders, preventing standard pr

Reinforcing Egocentric Spatial Perception in Multimodal Large Language Models via Ego Scene Augmentation

model-releasesarxiv-cs-cv

arXiv:2607.14497v2 Announce Type: replace Abstract: Egocentric Visual Question Answering (VQA) has attracted widespread attention as an important task for enabling Multimodal Large Language Models (ML

Reliable Neural Collapse Approximation for Open-World Test-Time Adaptation

arXiv:2608.19890v1 Announce Type: new Abstract: Test-Time Adaptation (TTA) methods aim to bridge the domain gap between the source and target domains. However, traditional TTA methods become ineffecti

researcharxiv-cs-lg

Applications

Robust Incomplete Multimodal Sentiment Analysis via Iterative Proxy Correction

arXiv:2608.19971v1 Announce Type: new Abstract: Multimodal sentiment analysis aims to infer affective states by integrating language, visual, and acoustic cues. However, real-world multimodal inputs a

applicationsarxiv-cs-cl

Robust Metaheuristics under Uncertainty for Berth Allocation and Quay Crane Assignment: A Review

arXiv:2608.19214v1 Announce Type: new Abstract: The berth allocation and quay crane assignment problem (BACAP) is a representative port-terminal scheduling problem in maritime transportation and freig

Scientific Data Skills: Enabling Agent-Ready Scientific Data Services at Scale

arXiv:2608.19625v1 Announce Type: new Abstract: Scientific data are increasingly used by AI agents, yet existing dataset representations provide limited support for autonomous discovery, interpretatio

STEP: Score-Based Temporal Energy for Human Pose Video Anomaly Detection

model-releasesarxiv-cs-cv

arXiv:2608.19987v1 Announce Type: new Abstract: Skeleton-based Video Anomaly Detection (VAD) offers a robust, privacy-preserving solution for identifying abnormal behaviors. To model the distribution

Agents

The Third Restructuring of Software Form: From the Three-Tier Architecture to Storage, Models, and Agents

arXiv:2608.20201v1 Announce Type: new Abstract: Software form has undergone two paradigm shifts since its inception: Software 1.0, in which instructions determine behavior, and Software 2.0, in which

agentsarxiv-cs-ai

Time-Series Retrieval for Grounding Multimodal Language Models in Remaining Useful Life

arXiv:2608.19218v1 Announce Type: cross Abstract: Large language models (LLMs) and agentic AI systems are increasingly being explored for domain-specific maintenance and prognostics tasks, raising the

Towards Audio Token Compression in Large Audio Language Models

arXiv:2511.20973v2 Announce Type: replace-cross Abstract: Large Audio Language Models (LALMs) deliver strong performance across speech and audio tasks, but their audio encoders generate high-rate toke

researcharxiv-cs-ai

Towards Efficient Pareto Set Approximation via Mixture of Experts Based Model Fusion

arXiv:2406.09770v2 Announce Type: replace-cross Abstract: Solving multi-objective optimization problems for large deep neural networks is a challenging task due to the complexity of the loss landscape

Towards Formalizing Reinforcement Learning Theory: A Robbins-Siegmund Approach

arXiv:2511.03618v2 Announce Type: replace Abstract: In this paper, we formalize the almost sure convergence of Q-learning and linear temporal difference (TD) learning with Markovian samples using the

researcharxiv-cs-lg

Towards general embodied intelligence: integrating large language models, knowledge bases, and reasoning capabilities to build the next generation of AI agents

arXiv:2608.19794v1 Announce Type: new Abstract: The convergence of large language models (LLMs), structured knowledge bases (KBs), and reasoning ability (RA) presents a promising trajectory toward gen

Applications

TT-net: Quantum Inspired Tensor Network Denoising in Conditional GANs

arXiv:2608.19789v1 Announce Type: new Abstract: Developed as a workhorse for classical simulations of quantum algorithms and quantum many-body systems, Tensor Network methods have entered the scientif

applicationsarxiv-cs-ai

Virtual Sensing to Enable Real-Time Monitoring of Inaccessible Locations & Unmeasurable Parameters

arXiv:2412.00107v3 Announce Type: replace-cross Abstract: Real-time monitoring of safety-critical interior states is an open problem across energy, environmental and industrial systems where direct in

VQC-ZTI: Variational Quantum Control for Zero Trust Protection of the Tactile Internet

arXiv:2608.18572v1 Announce Type: cross Abstract: Tactile Internet services couple cyber events directly to physical actuation, so security decisions must improve risk discrimination without perturbin

safetyarxiv-cs-lg

When Text and Numbers Disagree: Evidence Arbitration in Large Language Models

model-releasesarxiv-cs-cl

arXiv:2608.20116v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used in settings where textual summaries, numerical observations, and external tool outputs may provide co

Your Turn: At Home Turning Angle Estimation for Parkinson's Disease Severity Assessment

arXiv:2408.08182v5 Announce Type: replace-cross Abstract: People with Parkinson's Disease (PD) often experience progressively worsening gait, including changes in how they turn around, as the disease

A single design choice determines whether machine learning models of materials make physically impossible predictions

arXiv:2608.18714v1 Announce Type: cross Abstract: Machine-learned models are replacing first-principles calculations across materials discovery, and physical symmetry is the central guarantee built in

tutorialsarxiv-cs-lg

Agents

Adversarial Review: Structured Disagreement for Grounded Agentic Code Review

arXiv:2608.18167v1 Announce Type: new Abstract: Early multi-agent LLM systems often used role-separated teams, yet scaling agent count yields diminishing returns on repository-level coding tasks. Rece

agentsarxiv-cs-ai

AlphaClifford: Efficient Clifford Synthesis and Transpilation with Model-based RL

arXiv:2608.18946v1 Announce Type: cross Abstract: Clifford circuits play a foundational role in quantum computing, particularly due to their importance in quantum error correction and fault-tolerant l

researcharxiv-cs-ai

Beyond Predictive Fairness: Quantifying Attribution Consistency Across Demographic Groups in Diabetic Retinopathy Screening

arXiv:2608.18759v1 Announce Type: cross Abstract: Fairness in medical imaging is commonly evaluated through subgroup performance metrics, yet it remains unclear whether models rely on consistent visua

Bidirectional representational alignment between biological and artificial neural networks

arXiv:2608.18244v1 Announce Type: cross Abstract: Recent work has shown that representational alignment between biological and artificial neural networks is asymmetric: model representations predict n

Can a Lightweight Multimodal Model Estimate LLM Reasoning Performance? A Study for Compute-Optimal Document Inference

arXiv:2608.18591v1 Announce Type: new Abstract: Uniformly allocating inference reasoning budgets to LLMs is expensive and prone to over-thinking penalties; especially in document tasks where visual la

Applications

Candidate-Fate Accounting for Transparent Sensor Diagnostic Pipeline Search

arXiv:2608.18665v1 Announce Type: new Abstract: Industrial sensor diagnostics relies on preprocessing, representation, and classification pipelines, making automated pipeline search useful for reducin

applicationsarxiv-cs-ai

Agents

CentaurBench: Benchmarking LLM Capabilities on Augmenting vs. Automating Real-World Work Tasks

arXiv:2608.18554v1 Announce Type: cross Abstract: Most LLM benchmarks rank models on their ability to automate work tasks. In practice, however, models are often used to assist other (human or LLM) ag

agentsarxiv-cs-ai

Clinically Structured Surrogate Rewards for Post-SFT Medical Image Captioning

arXiv:2608.18654v1 Announce Type: new Abstract: Medical image captioning requires translating heterogeneous visual evidence into concise clinical descriptions, where errors in findings, assertion stat

safetyarxiv-cs-cv

Composed Historical Image Retrieval by Modeling Temporal Representations

arXiv:2608.18694v1 Announce Type: cross Abstract: While time evolves linearly, the geometry of neural embedding spaces is inherently multi-dimensional, often chaotic, and difficult to interpret. In pr

DART-SD: Diamond-topology Aware Retrieval and Tuning for Self-Distillation of Multi-Turn Tool-Calling Agents

arXiv:2608.18524v1 Announce Type: cross Abstract: Equipping Large Language Models (LLMs) with multi-turn tool-calling capabilities is essential for building autonomous agents. However, progress is fun

Debiased Inference for AI-Generated Data without Gold-Standard Labels: Identification via Multiple Imperfect Measurements

arXiv:2608.18294v1 Announce Type: cross Abstract: An increasing number of scholars use AI to measure variables they subsequently include in downstream analyses. Although AI-measured variables are ofte

DynCur-Geo: Dynamic Curiosity Reward Shaping for Multimodal Active Geo-Localization

arXiv:2608.18673v1 Announce Type: new Abstract: Active geo-localization enables low-altitude UAVs to search for specified targets from limited local aerial observations, supporting time-sensitive appl

safetyarxiv-cs-cv

Evaluation of Image Matching Methods for Visual Odometry on UAVs

arXiv:2608.18624v1 Announce Type: new Abstract: Unmanned aerial vehicles (UAVs) are becoming a powerful tool for many environmental monitoring and transport applications. Yet, their reliance on Global

researcharxiv-cs-cv