Search: “evaluation”

FedTransKD-IDS: Robust Federated Transfer Learning with Knowledge Distillation for Intrusion Detection in IoT

arXiv:2608.06447v1 Announce Type: cross Abstract: In modern distributed network environments, particularly in Internet of Things infrastructures and 5G networks, stringent privacy preservation and sca

researcharxiv-cs-lg

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Finding Usable Weight Mechanisms with Tiled SVD

DGX agent

arXiv:2608.06969v1 Announce Type: new Abstract: The dominant approach to mechanistic interpretability trains proxy dictionaries such as sparse autoencoders and labels features from max-activating text

model-releasesarxiv-cs-ai

10 Aug 2026

Fixed and Adaptive Topological DeepONets: Functional Measurements on Hausdorff Locally Convex Spaces

arXiv:2608.06428v1 Announce Type: new Abstract: Deep Operator Networks (DeepONets; arXiv:1910.03193) typically encode an input function through point values on a fixed discretization. Building on the

local-aiarxiv-cs-lg

Flowing Through States: Neural ODE Regularization for Reinforcement Learning

arXiv:2608.06595v1 Announce Type: cross Abstract: Neural networks applied to sequential decision-making tasks typically rely on latent representations of environment states. While environment dynamics

FutureBridge: Token Selection Beyond Local Preference in Collaborative Decoding

arXiv:2608.06819v1 Announce Type: cross Abstract: Token-level collaboration allows a large language model (LLM) to assist a small language model (SLM) when their predictions diverge. Existing methods

local-aiarxiv-cs-ai

Game-Theoretic Inverse Reinforcement Learning for Modeling Competitive Human Driving: A Cut-in Prediction Study

model-releasesarxiv-cs-lg

arXiv:2608.06445v1 Announce Type: cross Abstract: Capturing the strategic decision-making inherent in competitive human driving is critical for autonomous vehicle safety and traffic simulation. This s

Geo-Spatial Concept Probing of Large Language Models: Abstraction, Compositionality, and Grounding

arXiv:2608.07353v1 Announce Type: cross Abstract: Understanding concepts is fundamental to generalization. Despite their impressive performance on a wide range of tasks, Large Language Models (LLMs) s

GeoDistill-Refine: Silhouette-First Geometry Distillation for Annotation-Free Spacecraft Segmentation

arXiv:2608.07405v1 Announce Type: cross Abstract: Foundation segmentation models can provide supervision for spacecraft imagery without manual training masks, but their predictions vary with textual p

Grad-ECLIP: Gradient-based Visual and Textual Explanations for CLIP

arXiv:2502.18816v3 Announce Type: replace Abstract: Significant progress has been achieved on the improvement and downstream usages of the Contrastive Language-Image Pre-training (CLIP) vision-languag

safetyarxiv-cs-cv

Graph Machine: Exploring Edge Mechanisms as an Inductive Bias

arXiv:2608.06834v1 Announce Type: new Abstract: Transformers provide a powerful architecture for global content-based matching, but reasoning problems may benefit from a stronger inductive bias toward

safetyarxiv-cs-lg

HazeSpikeMamba: Coupling Spiking-Inspired and State-Space Features for Self-Supervised Real-World Dehazing

arXiv:2608.06886v1 Announce Type: new Abstract: Dehazing networks are commonly trained on synthetic hazy-clear pairs, but their performance often drops on real photographs. Synthetic haze generated us

local-aiarxiv-cs-cv

HLSmith: An Expert-Guided Agentic Framework for C/C++-to-HLS Translation

arXiv:2608.06791v1 Announce Type: cross Abstract: Application-specific FPGA accelerators offer substantial performance and energy-efficiency gains across many application domains, but developing them

I Seek You in Videos: Identity-Conditioned Queries for Person-Centric Video Reasoning

arXiv:2608.07417v1 Announce Type: cross Abstract: Real-world video reasoning often involves multimodal, multi-source inputs, whereas existing video reasoning tasks typically assume a simplified video-

IB-RL: Isolated Bilateral Reinforcement Learning for Strategic Dialogue Agents

arXiv:2608.06735v1 Announce Type: new Abstract: Reinforcement learning (RL) has achieved strong results in improving large language models (LLMs) on tasks with stationary, verifiable rewards, such as

Applications

Improving Low-Resolution Face Recognition under Limited Data: How Synthetic Data Generation Can Close the Domain Gap

arXiv:2608.06580v1 Announce Type: new Abstract: Face Recognition (FR) systems in surveillance settings often encounter Low Resolution (LR) faces, those whose face region falls below the standard 112 i

applicationsarxiv-cs-cv

Improving Performance of Spike-based Deep Q-Learning using Ternary Neurons

arXiv:2506.03392v2 Announce Type: replace Abstract: We propose a new ternary spiking neuron model to improve the representation capacity of binary spiking neurons in deep Q-learning. Although a ternar

safetyarxiv-cs-lg

Index SLM Technical Report

arXiv:2607.09885v2 Announce Type: replace Abstract: We present Index-1.9B, a series of open small language models developed at Bilibili. The series comprises four models: Index-1.9B-Base, a foundation

Interpretable reinforcement learning with decision-tree pruning

arXiv:2608.07151v1 Announce Type: cross Abstract: Reinforcement learning policies are difficult to inspect, but interpreting them is a prerequisite for trustworthiness. Converting a trained policy int

INTRYGUE: Induction-Aware Entropy Gating for Reliable RAG Uncertainty Estimation

arXiv:2603.21607v2 Announce Type: replace Abstract: While retrieval-augmented generation (RAG) significantly improves the factual reliability of LLMs, it does not eliminate hallucinations, so robust u

Is Forward Prediction Enough? Physical State Grounding for JEPA World Models

arXiv:2608.06799v1 Announce Type: cross Abstract: Learning structured and control-relevant latent representations remains a key challenge for world models. Recent JEPA-based world models learn action-

safetyarxiv-cs-cv

Iterative Training of Physics-Informed Neural Networks with Fourier-enhanced Features

model-releasesarxiv-cs-lg

arXiv:2510.19399v2 Announce Type: replace Abstract: Spectral bias, the tendency of neural networks to learn low-frequency features first, is a well-known issue with many training algorithms for physic

Latent Fact-Checking: Detecting Misinformation through Activation Engineering

arXiv:2608.06417v1 Announce Type: cross Abstract: The proliferation of misinformation online has driven demand for scalable detection systems. While most existing approaches rely on surface-level ling

LitTraceQA: A Benchmark for Multi-Stage Grounding and Verification in Scientific Question Answering

arXiv:2608.07370v1 Announce Type: new Abstract: Scientific literature is increasingly used as a knowledge source for language models, retrieval-augmented generation systems, and research assistants, b

Tutorials

LoRAScan: Detecting Backdoor Prompts in Low-Rank Adapters for Large Language Models via Down-Projection Activation Spikes

arXiv:2608.06795v1 Announce Type: cross Abstract: Low-rank adaptation (LoRA) enables efficient specialization and distribution of large language models through compact adapters. However, untrusted ada

tutorialsarxiv-cs-ai

Lost in Interpolation: Why Predictive Feedback Fails in Diffusion Language Models

arXiv:2608.06529v1 Announce Type: new Abstract: Soft-masking accelerates the convergence of Masked Diffusion Language Models (MDLMs). Existing formulations build this blend with linear interpolation (

LSEAD: A Privacy-Preserving LLM-Based Speech Analysis Framework for Early Alzheimer's Disease Screening

arXiv:2608.07378v1 Announce Type: cross Abstract: Early diagnosis of Alzheimer's disease (AD) is critical for enabling timely interventions that may slow disease progression and improve patient outcom

LyEvO: Lyapunov-Guided Evolutionary Optimization for Safe and Robust Sim-to-Real Policy Learning

arXiv:2608.06481v1 Announce Type: cross Abstract: Training controllers that are safe and robust in simulation, and systematically assessing their readiness for real-world deployment, remain key challe

MaskFlow: Precise, Consistent and Seamless Regional Image Editing

arXiv:2608.06929v1 Announce Type: cross Abstract: Regional image editing has attracted considerable attention for its spatial controllability. Although instruction-based and mask-reference-based editi

MemOPD: On-Policy Distillation through Memory State Alignment for Long-Horizon Agents

arXiv:2608.07068v1 Announce Type: new Abstract: Long-horizon agents accumulate growing contexts during interaction, impairing performance and stability. Compact memory mitigates this problem by compre

MemWM: Memory-Augmented Text-Based World Model

arXiv:2608.07107v1 Announce Type: new Abstract: World models are increasingly used to support planning in agents by predicting how environment states evolve in response to agent actions. Yet fluent ne

Model Confidence Under Answer-Preserving Attacks: An Informativeness-Manipulability Frontier

arXiv:2608.06571v1 Announce Type: cross Abstract: Deployed vision-language systems often gate their answers on confidence, making confidence robustness relevant to oversight. We study confidence reado

MolBioKG: Grounding Out-of-Graph Molecules in Biomedical Knowledge Graphs via Multi-Resolution Structural Anchoring

arXiv:2608.06713v1 Announce Type: new Abstract: Biomedical knowledge graphs (KGs) accelerate drug discovery, but standard pipelines assume query molecules already exist as graph entities, leaving unre

Momba: Network Modernization Improves Multi-Objective Reinforcement Learning

arXiv:2608.07180v1 Announce Type: cross Abstract: Recent advances in deep reinforcement learning (RL) have shown that improving neural network architectures can yield substantial gains in sample effic

MotionStrata: Hierarchical Motion Latents for Compact Video Autoencoding

arXiv:2506.07136v2 Announce Type: replace Abstract: First-frame-conditioned video autoencoders represent a clip with persistent content and a compact motion code. Although this removes much of the app

researcharxiv-cs-cv

Multi-Agent Forensic Reasoning for Generalizable Deepfake Video Detection

arXiv:2608.06865v1 Announce Type: cross Abstract: The malicious use of generative artificial intelligence to create highly realistic deepfake videos raises serious ethical concerns and poses substanti

Multi-Level Modeling of Large Language Model Inference Latency and Energy via Hybrid Analytical--Machine-Learning Predictors

arXiv:2608.06723v1 Announce Type: cross Abstract: The rapid scaling of Large Language Models (LLMs) has significantly increased computational cost, energy consumption, and inference latency, making ac

Newton-Schulz Retraction-Based Inference Enables Hidden Quantum Markov Models to Outperform Classical HMMs

model-releasesarxiv-cs-lg

arXiv:2608.06554v1 Announce Type: new Abstract: Hidden Markov models (HMMs) are widely used probabilistic models for discrete sequential data but can be limited when hidden dynamics are complex. Hidde

Online Conformal Prediction Beyond Feedback

arXiv:2608.07139v1 Announce Type: new Abstract: Uncertainty quantification is essential when deploying machine learning models in safety-critical applications. Online conformal prediction (OCP) provid

safetyarxiv-cs-lg

Online Monitoring and Corrective Steering of Programming Agents

arXiv:2608.06701v1 Announce Type: cross Abstract: Fixing GitHub issues in large-scale projects is a long-horizon task, especially when a fix requires changes across multiple locations or the issue des

local-aiarxiv-cs-ai

Optimizing Spectral Prediction in MXene-Based Metasurfaces Through Multi-Channel Spectral Refinement and Savitzky-Golay Smoothing

arXiv:2602.08406v2 Announce Type: replace-cross Abstract: The prediction of electromagnetic spectra for MXene-based solar absorbers, where MXenes are a family of two-dimensional transition metal carbi

Panoramic Multimodal Semantic Occupancy Prediction for Quadruped Robots

model-releasesarxiv-cs-cv

arXiv:2603.13108v2 Announce Type: replace-cross Abstract: Panoramic imagery provides holistic 360{eg} visual coverage for environmental perception in quadruped robots. However, existing occupancy pred

Pathryoshka: Compressing Pathology Foundation Models via Multi-Teacher Knowledge Distillation with Nested Embeddings

arXiv:2511.23204v2 Announce Type: replace Abstract: Pathology foundation models (FMs) have driven significant progress in computational pathology. However, these high-performing models can easily exce

researcharxiv-cs-cv

Post-Grokking Collapse at the Representation-Readout Interface in Muon-Trained Transformers

arXiv:2608.07436v1 Announce Type: new Abstract: Under the standard split, Muon gets hidden matrices and AdamW embeddings/output head. Muon groks modular addition faster, but its solutions do not hold.

Progress-Certified Reversible Simplex Supervision of Goal-Reaching Reinforcement Learning

arXiv:2601.19499v2 Announce Type: replace Abstract: Task completion is difficult to certify when state aggregation, model mismatch, and disturbances invalidate nominal RL transitions. We present a rev

safetyarxiv-cs-ro

PsychoAgent: An Affect-Sensitive Cognitive Architecture for Conflict-Aware Memory in LLM Agents

arXiv:2608.07438v1 Announce Type: new Abstract: Human-like cognition does not select past experience by topical similarity alone: affective significance and unresolved conflict also shape what becomes

PURe: A Plug-and-Play Product-Unit Residual Module for Vision Networks

arXiv:2505.04397v3 Announce Type: replace-cross Abstract: Modern vision networks are dominated by additive local transformations, whereas explicit multiplicative local interactions remain underexplore

Quantization Damage Is Multiplicative, Not Additive

arXiv:2608.06564v1 Announce Type: cross Abstract: Quantization is how large language models are actually deployed, and below four bits it is known to hurt. What nobody can say is which of the model's

Reading Copom's Tone: A Weighted LLM Framework for Hawkish-Dovish Sentiment, Forward Guidance, and Uncertainty

arXiv:2608.07251v1 Announce Type: cross Abstract: This paper documents an applied natural-language-processing framework for measuring the tone of Brazilian Monetary Policy Committee (Copom) statements