Search: “framework”

Language Equality has a Price: A Systematic Investigation of Multi-turn LLM Performance for EU-24+

arXiv:2608.01395v1 Announce Type: new Abstract: We evaluate large language models (LLMs) as language agents playing goal-directed dialogue games in self-play across 30 languages: the 24 official EU la

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Latent-Regime Bias Auditing for Volatility Forecasting

DGX agent

arXiv:2608.01599v1 Announce Type: new Abstract: Volatility forecasts are commonly evaluated with aggregate accuracy metrics such as RMSE and MAE, but these metrics can hide conditional failures that m

safetyarxiv-cs-lg

4 Aug 2026

LeapTalk: Breaking the Latency-Quality Trade-off in Talking Head Generation

arXiv:2608.00079v1 Announce Type: new Abstract: Long-form and real-time talking-head generation remains challenging due to a latency-quality trade-off: inefficient multi-step diffusion prohibits strea

Learning the Pareto Frontier of Predictive Models under Distribution Shift

arXiv:2608.00632v1 Announce Type: new Abstract: Modern machine learning pipelines increasingly rely on reusing pretrained and foundation models across downstream tasks. These pretrained models can dif

applicationsarxiv-cs-lg

LLM generation novelty through the lens of semantic similarity

arXiv:2510.27313v3 Announce Type: replace-cross Abstract: Generation novelty is a key indicator of an LLM's ability to generalize, yet measuring it against full pretraining corpora is computationally

Loanword or Switch? The Annotation Boundary, Not the Model, Drives Kazakh-Russian Code-Switching Identification

arXiv:2608.00581v1 Announce Type: new Abstract: Off-the-shelf LID and letter heuristics over-label Kazakh-Russian social text as mixed: Russian loanwords inside Kazakh look like code-switching under a

Long-Horizon Embodied Decision-Making via Multimodal Memory Compression

arXiv:2608.01456v1 Announce Type: cross Abstract: Agents are increasingly expected to act not only as task executors, but also as decision-makers on behalf of human users. This shift requires agents t

Loop-Mamba: A Loop Mamba with Degradation-Aware and Shared Memory for Old Photo Restoration

arXiv:2608.02346v1 Announce Type: new Abstract: Old photographs often suffer from multiple coupled degradations, including scratches, cracks, fading, blur, noise, and missing regions, severely degradi

Mapping melliferous tree species in Kenya via one-class classification with hyperspectral unsupervised domain adaptation

arXiv:2608.02045v1 Announce Type: cross Abstract: The beekeeping sector holds significant potential for livelihood diversification among the agropastoral communities in Kenya. Melliferous tree species

MetaRoute-Bench: Evaluating Meta-Decision Policies for Agentic Workflow Routing

arXiv:2608.00107v1 Announce Type: new Abstract: Agentic systems must repeatedly decide whether to answer directly, decompose a task, invoke a tool, execute code, delegate to a specialist, verify an in

Model-Agnostic FDR Control via Group Gaussian Mirror and Permutation SHAP

arXiv:2608.00989v1 Announce Type: cross Abstract: Most FDR-controlled feature selection methods are designed for coordinate-wise hypotheses, where each feature has a single weight or importance score.

applicationsarxiv-cs-lg

Tutorials

Modeling Unknown Nonlocal PDE Systems via Flow Map Learning

arXiv:2608.00400v1 Announce Type: new Abstract: Nonlocal partial differential equations arise in many applications but are often difficult to model and learn because of the presence of nonlocal operat

tutorialsarxiv-cs-lg

Motion Planning for Mobile Manipulators Navigating Doorways via Model Predictive Control

arXiv:2608.00206v1 Announce Type: new Abstract: Navigating doorways is a fundamental capability for mobile manipulators operating in human environments, requiring coordinated motion between the mobile

researcharxiv-cs-ro

Neural Circuit Function Inference with LLMs

arXiv:2608.00059v1 Announce Type: new Abstract: The success of connectome mapping now shifts the challenge of understanding the nervous system to the interpretation of neural circuits. Here, we devise

Nonlinear Laplacians Improve Signed-Directed Graph Learning

arXiv:2608.00836v1 Announce Type: new Abstract: While signed-directed graphs have been studied using linear Laplacians in the design of graph neural networks, relatively little research has focused on

researcharxiv-cs-lg

Optical Flow from Photons

arXiv:2608.00499v1 Announce Type: new Abstract: Optical flow remains challenging in high-speed and low-light scenes, where the limited frame rate and sensitivity of conventional cameras lead to motion

applicationsarxiv-cs-cv

ORCA: ORgan-Centroid Aggregation for Training-Free 3D CT Visual Token Compression

arXiv:2608.00345v1 Announce Type: new Abstract: A 3D CT scan entering a vision-language model produces a long sequence of visual tokens, often thousands to tens of thousands per volume, and this seque

PNEC-Mamba: Prototype-Guided Positive-Negative Evidence Calibration for Hyperspectral Image Classification

arXiv:2608.01910v1 Announce Type: new Abstract: In real-world hyperspectral scenes, pixel representations are often ambiguous due to factors such as spectral similarity, mixed pixels, and local contex

Progressive^2: A Teacher-Student Progressive Co-Evolving Knowledge Distillation Method for Substantial Model Compression

arXiv:2608.00129v1 Announce Type: new Abstract: Knowledge distillation (KD) is a widely utilized technique for transferring knowledge from a large model (the teacher) to a smaller model (the student).

researcharxiv-cs-lg

Provably Safe Generative Sampling with Constricting Barrier Functions

arXiv:2602.21429v3 Announce Type: replace Abstract: Flow-based generative models, such as diffusion models and flow matching models, have achieved remarkable success in learning complex data distribut

safetyarxiv-cs-lg

PyDPF: A Python Package for Differentiable Particle Filtering

arXiv:2510.25693v3 Announce Type: replace-cross Abstract: State-space models (SSMs) are a widely used tool in time series analysis. In the complex systems that arise from real-world data, it is common

applicationsarxiv-cs-lg

RadYOLO: Computationally Efficient 3D Object Detection and Segmentation in CT and MRI

arXiv:2608.00508v1 Announce Type: new Abstract: Object detection and segmentation in three-dimensional medical images is a very active area of research. However, most proposed deep learning models car

local-aiarxiv-cs-cv

Rethinking and formalising the state across languages: a unified computational learning theory account

arXiv:2608.00523v1 Announce Type: new Abstract: The linguistic notion of state has traditionally been restricted to the construct (annexation) state of Afroasiatic languages and treated as a language-

RH-RAG: Trustworthy Long-Form Generation for Privacy-Constrained Settings

arXiv:2608.01311v1 Announce Type: new Abstract: Generating long-form content from extensive internal reports remains challenging for organizations operating under strict privacy and security constrain

local-aiarxiv-cs-cl

Right Answer, Wrong Method: Shortcut Hacking Misleads the Evaluation of LLM Reasoning on Frontier Science Benchmarks

arXiv:2608.02442v1 Announce Type: cross Abstract: Scientific reasoning benchmarks typically evaluate large language models (LLMs) using final-answer accuracy. However, a correct answer does not necess

RING: Retrieval-Internalized Generation for Continual Large-Scale Knowledge Injection

arXiv:2608.01630v1 Announce Type: new Abstract: Retrieval-augmented generation (RAG) improves factuality but adds latency and engineering overhead at serving time. We propose RING (Retrieval-Internali

Score-Based Turbo Message Passing for Plug-and-Play Compressive Imaging

arXiv:2512.14435v2 Announce Type: replace Abstract: Message-passing algorithms have been adapted for compressive imaging by incorporating various off-the-shelf image denoisers. However, these denoiser

Scoring Rules! Statistical and Strategic Alignment for Text Evaluation Metrics

arXiv:2608.01423v1 Announce Type: cross Abstract: Reference-based text evaluation metrics, which are widely used to assess natural language generation systems, score a candidate response by comparing

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Self-composing neural operators for high-frequency and multiscale PDE surrogates

arXiv:2508.20650v2 Announce Type: replace Abstract: Addressing the computational challenges of high-frequency and multiscale partial differential equations (PDEs), this work introduces a self-composin

SG-WAM: Self-Guided World Modeling in Geometry-Aware Policy Space

arXiv:2608.01397v1 Announce Type: cross Abstract: World Action Models (WAMs) couple action generation with prediction of future states. Their effectiveness depends on whether future dynamics are model

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Similarity Weighted Aggregation with Global Differential Privacy for Federated Brain Lesion Segmentation

arXiv:2608.00872v1 Announce Type: cross Abstract: Federated Learning (FL) enables collaborative training of machine learning models across multiple institutions without sharing sensitive data, making

Sixteen models, fewer than two voices: measuring ensemble dispersion where no answer is uniquely correct

arXiv:2608.00285v1 Announce Type: new Abstract: Sixteen language models drawn from ten families produced, on average, the semantic diversity of 1.69 distinct formulations of a psychotherapeutic case,

Spatiotemporal Proximal Causal Inference under Hidden Confounding and Interference

arXiv:2608.01352v1 Announce Type: new Abstract: Estimating causal effects from real-world spatiotemporal data is challenging due to hidden confounders and interference. Standard causal identification

local-aiarxiv-cs-lg

SphereVideo: Prototype-anchored Hyperspherical Boundary for Continual AI-generated Video Detection

arXiv:2608.01334v1 Announce Type: new Abstract: AI-generated video (AIGV) detection aims to distinguish real videos from AI-generated ones. In practice, detectors trained on existing data often fail t

STEAM:ASpatio-TEmporal Alignment Mixture-of-Experts Model with Hierarchical Pre-training for EEG Decoding

arXiv:2608.02070v1 Announce Type: new Abstract: Brain-computer interfaces (BCIs) have been widely used in motor rehabilitation, disease diagnosis, and other neural engineering scenarios. However, conv

safetyarxiv-cs-cv

T^2exture: Sparsely Perturbed Thermal-to-Texture Imaging

arXiv:2608.02192v1 Announce Type: new Abstract: Thermal imaging remains effective under adverse illumination, yet passive long-wave infrared (LWIR) measurements often lack fine texture. Existing therm

Test-Time Curriculum for Open-Set AIGC Detection

arXiv:2608.00559v1 Announce Type: new Abstract: AI-generated image detectors deployed in open-world environments inevitably face distribution shifts as new and stronger generative models continue to e

Tevatron Meets Megatron: Expert-Parallel LLM Reranker Training on an Academic Budget

arXiv:2608.00916v1 Announce Type: cross Abstract: Modern reranking recipes---billion-scale cross-encoders, mixture-of-experts (MoE) backbones, and distillation against strong teachers---have outpaced

The Bayesian Reflex: A Predictive Coding Engine for Artificial Intelligence

arXiv:2608.00492v1 Announce Type: cross Abstract: Predictive coding offers a powerful theory of cortical computation, but corresponding scalable algorithmic implementations for artificial intelligence

researcharxiv-cs-lg

Track-Guided Hierarchical Reinforcement Learning for Autonomous Vehicle Drifting with Minimum-Lap-Time Planning

arXiv:2608.00113v1 Announce Type: new Abstract: In Formula 1, drivers optimize racing lines within tire grip limits to minimize lap times; however, in rally racing, drivers intentionally break tractio

safetyarxiv-cs-ro

TreeProbe : A Tibetan Medicine Benchmark for Cultural Bias in LLMs

arXiv:2608.00640v1 Announce Type: new Abstract: Large language models are increasingly viewed as a potential means of mitigating global health inequities, yet their outputs often reflect dominant high

Tunneling the Loss Landscape: Bypassing Memorization with Monte Carlo Parameter Swapping

arXiv:2608.01833v1 Announce Type: cross Abstract: Grokking is a striking phenomenon in neural network training, where a model can undergo a prolonged period of pure memorization before abrupt generali

Two-Stage Bengali Sentiment Classification: Domain Adaptation Through Continual Learning and Parameter-Efficient Fine-Tuning

arXiv:2608.01471v1 Announce Type: new Abstract: Understanding sentiment in low-resource languages remains a key challenge for Natural Language Processing (NLP), particularly when domain-specific data

UCBound-Net: Uncertainty-Guided Boundary-Aware Continual Learning for Domain-Incremental Ultrasound Segmentation

arXiv:2608.01518v1 Announce Type: new Abstract: Continual learning in clinical imaging faces a dual challenge: a model must assimilate knowledge from new anatomical domains while retaining representat

Agents

UEmbed: Unified Sparse and Dense Multimodal Embeddings

arXiv:2608.02583v1 Announce Type: cross Abstract: Sparse retrieval underpins modern search systems, from web search to retrieval-augmented generation. Existing work has introduced Learned Sparse Retri

agentsarxiv-cs-cl

Uncertainty-Aware Simulation-Based Inference for Operations Research with Large Language Models

arXiv:2608.00019v1 Announce Type: new Abstract: Deploying large language models (LLMs) for operations research (OR) tasks remains challenging because correctness depends on a coherent modeling process

local-aiarxiv-cs-lg

Uncovering and Mitigating Positional Blind Spots in Vision-Language-Action Models

arXiv:2608.01573v1 Announce Type: new Abstract: Recent Vision-Language-Action (VLA) models achieve promising performance in robotic manipulation, typically measured by success rates aggregated over pr

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Tutorials

Unleashing the Power of Text: Text-Guided Flow Matching for Image Fusion under Complex Degradations

arXiv:2608.00530v1 Announce Type: new Abstract: Infrared-visible image fusion under realistic degradation scenarios is a challenging task, as degradations not only cause a loss of reliable modality-sp

tutorialsarxiv-cs-cv