Search: “models”

Recovery Rates Are Not Comparable Across Transcription Factors: Chance Correction for Attribution Evaluation

arXiv:2609.16271v1 Announce Type: cross Abstract: Attribution methods for genomic sequence models are commonly evaluated by how much of a known motif they recover, or by how a prediction degrades as e

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Research

ReMova: Fine-tuning LLMs for English to Belarusian translation

DGX agent

arXiv:2609.16427v1 Announce Type: new Abstract: This paper presents a Belarusian-specific data-cleaning pipeline and fine-tuning for English-Belarusian machine translation. Our cleaning pipeline disti

researcharxiv-cs-cl

16 Sept 2026

RoofSeg: An edge-aware transformer-based network for end-to-end roof plane segmentation

arXiv:2508.19003v2 Announce Type: replace-cross Abstract: Roof plane segmentation is one of the key procedures for reconstructing three-dimensional (3D) building models at levels of detail (LoD) 2 and

Shared-Prefix KV Reuse Across Standard LoRA Adapters: Quality and Serving Tradeoffs

arXiv:2609.17109v1 Announce Type: new Abstract: A common small-model deployment runs one shared backbone with several LoRA specialists that answer over the same context. Serving them naively re-prefil

Symmetry-Aware Likelihood-Orbit Aggregation for Selective Left-Right Claim Verification

arXiv:2609.17004v1 Announce Type: new Abstract: Frozen vision-language models (VLMs) remain unreliable on fine-grained left-right claims, and raw claim likelihoods need not reliably rank verification

researcharxiv-cs-cv

The Latent That Never Was: A Forensic Re-run of the CVAE Ablation in Action Chunking Transformer

arXiv:2609.16745v1 Announce Type: cross Abstract: Action Chunking Transformers (ACT) are widely used to learn robot manipulation from demonstrations. Their conditional variational autoencoder includes

The Neverwhere Visual Parkour Benchmark Suite

model-releasesarxiv-cs-cv

arXiv:2609.16443v1 Announce Type: cross Abstract: State-of-the-art visual locomotion controllers are increasingly capable at handling complex visual environments, making evaluating their real-world pe

Towards Detecting AI-Assisted Responses in Online Surveys

model-releasesarxiv-cs-cl

arXiv:2609.17317v1 Announce Type: new Abstract: The use of LLMs to complete online surveys impacts the validity of survey-based research, but detecting such usage remains underexplored. We introduce a

Towards Scalable RLVR: Multimodal Instruction Following Data Synthesis and Distillation

arXiv:2609.16059v1 Announce Type: new Abstract: Multimodal instruction following (MMIF) is crucial for building generalist agents. However, current training paradigms rely heavily on Supervised Fine-T

safetyarxiv-cs-cl

Turn-level Multiscale Density Ratio Estimation for LLM Agents

arXiv:2609.16760v1 Announce Type: new Abstract: With the rapid development of Large language model (LLM), agent systems enhanced by LLMs show huge potential in being able to deal with complex tasks, e

safetyarxiv-cs-ai

Vroom-Vroom at SHROOM-Visions: A Multi-Judge Committee for Detecting Hallucinated Spans in Vision-Language Outputs

arXiv:2609.17327v1 Announce Type: cross Abstract: This paper describes our submission to the SHROOM-Visions shared task on detecting and classifying hallucinated character spans in vision-language mod

What Breaks Local Watermarks? A Robustness Benchmark for Local Invisible Image Watermarking

model-releasesarxiv-cs-ai

arXiv:2609.16832v1 Announce Type: cross Abstract: Local image watermarking embeds an invisible signal into selected image regions rather than spreading it across the entire image, enabling payload rec

You Don't Need To Train: Agentic Heuristic Learning Studio for Executable Human Activity Recognition

model-releasesarxiv-cs-ai

arXiv:2609.16065v1 Announce Type: cross Abstract: Human activity recognition (HAR) is usually framed as gradient-based training of neural networks. Agentic Heuristic Learning (AHL) Studio explores a c

A Comprehensive Review of Multimodal Facial State Analysis: Tasks, Methods, and Resources

arXiv:2609.13255v1 Announce Type: new Abstract: Facial state analysis plays a crucial role in understanding human expressions, psychological modeling, and human computer interaction. Traditional unimo

researcharxiv-cs-cv

A Corpus-Aligned Uthmani-to-Standard Quranic Word Mapping and a Deterministic Recitation Validator

model-releasesarxiv-cs-cl

arXiv:2609.14967v1 Announce Type: new Abstract: Quranic text is distributed in two orthographic forms that are byte-level distinct: the Uthmani script used in every printed mushaf, and the Standard (I

A derivative-fidelity failure mode in physics-informed neural networks: strengthened benchmark evidence from function-value training

arXiv:2609.13171v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) use automatic differentiation to impose differential-equation residuals, but good agreement in function values

A Functional SVD Framework for Regularized Multivariate Functional PCA with Dual Penalization

arXiv:2609.14815v1 Announce Type: cross Abstract: This paper introduces a novel framework for Regularized Multivariate Functional Principal Component Analysis (ReMFPCA) via Functional Singular Value D

Adaptive Phase-Switching for Communication-Efficient Federated LoRA Fine-Tuning

arXiv:2609.13512v1 Announce Type: cross Abstract: Federated fine-tuning of large language models with low-rank adaptation reduces per-client trainable parameters, but client-to-server communication re

Admissable: Training Reinforcement Learning Agents against Adversarial Missingness

arXiv:2609.15297v1 Announce Type: new Abstract: In order to make Reinforcement Learning algorithms applicable in real world scenarios, safety must be ensured even under adverse operating conditions. I

Algorithmic Information Dynamics of Learning: A Certified, Differentiable Complexity Controller for Grokking

arXiv:2609.13197v1 Announce Type: new Abstract: Algorithmic Information Dynamics (AID) studies systems by perturbing them and measuring changes in algorithmic complexity, but its usual estimator, the

Local Ai

Anatomical Grounding and Leakage-Aware Multimodal Contrastive Learning for Alzheimer's Disease Classification from Structural MRI

arXiv:2609.15888v1 Announce Type: cross Abstract: Deep networks trained on structural MRI for Alzheimer's disease (AD) staging often reach reasonable accuracy while attending to anatomically irrelevan

local-aiarxiv-cs-ai

Architecture--Optimization Co-Design for Physics-Informed Neural Networks via Layer-wise Coordinate Adaptation and Gradient Conflict Resolution

arXiv:2601.12971v2 Announce Type: replace Abstract: Physics-informed neural networks (PINNs) can be limited by coordinate representations and conflicting gradients from heterogeneous physical constrai

Are LLMs Good Financial User Simulators? A Preliminary Study

arXiv:2609.15727v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used as user simulators, but their ability to reproduce evolving individual financial decisions remains un

au-Elicitation: Benchmarking multi-turn entity extraction in voice agents

model-releasesarxiv-cs-ai

arXiv:2609.13602v1 Announce Type: new Abstract: Voice agents often need to collect names, addresses, identifiers, dates, and times exactly, yet end-to-end benchmarks obscure where capture fails. We in

Autoencoder-Based Parameter Estimation for Superposed Multi-Component Damped Sinusoidal Signals

arXiv:2604.03985v2 Announce Type: replace Abstract: Damped sinusoidal oscillations are widely observed in many physical systems, and their analysis provides access to underlying physical properties. H

BEACON: Behavior and Appearance Control for Subject-Specific Video Generation

arXiv:2609.13264v1 Announce Type: cross Abstract: Generating human-centric videos that preserve both visual identity and person-specific expressive behavior remains a fundamental challenge. In additio

Beyond Single-Axis Testing: Paired Evaluation of Compound Robustness in Vision-Language-Action Policies

model-releasesarxiv-cs-ro

arXiv:2609.15940v1 Announce Type: new Abstract: Vision-language-action policies are typically evaluated one perturbation at a time, providing a useful diagnosis of their sensitivity to individual dist

BIG-CBF: Behavior-Imagination-Guided Control Barrier Function with Shared Uncertainty for Mobile Robot Navigation

model-releasesarxiv-cs-ro

arXiv:2609.14343v1 Announce Type: new Abstract: Control barrier functions (CBFs) provide a mathematically grounded framework for enforcing local collision-avoidance constraints in autonomous mobile ro

BLInD: Learning Driver Intent as a Distribution over Future Ego Trajectories

arXiv:2609.13941v1 Announce Type: new Abstract: We present BLInD (Blind Learned Intent Distribution), a compact network that maps recent vehicle-state history (e.g. speed, curvature, indicator, and ve

safetyarxiv-cs-cv

Hardware

BOOST: Concurrent Access to Host Memory and HBM to Accelerate LLM Inference

arXiv:2609.13592v1 Announce Type: cross Abstract: GPU memory bandwidth and capacity limit throughput in large language model (LLM) inference. The GPU memory system consists of a primary tier of high-b

hardwarearxiv-cs-lg

Local Ai

Boosting Point-supervised Temporal Action Localization via Text Refinement and Alignment

arXiv:2602.01257v2 Announce Type: replace Abstract: Recently, point-supervised temporal action localization has gained significant attention for its effective balance between labeling costs and locali

local-aiarxiv-cs-cv

Bridging the Modality Gap in Long-Form Clinical Audio: A Comparative Study of Lightweight and Heavyweight End-to-End SOAP Generation

arXiv:2609.14467v1 Announce Type: cross Abstract: Automating clinical documentation from long-form doctor-patient conversations remains challenging for modern audio-language models. While cascaded ASR

Can We Trust the Judges? Validation of Factuality Evaluation Methods via Answer Perturbation

arXiv:2609.15561v1 Announce Type: new Abstract: Evaluating the factual correctness of large language models (LLMs) is vital for many applications. But are our evaluation tools themselves trustworthy?

researcharxiv-cs-cl

CANAL: Channel-Aware Noise Allocation for Differentially Private Feature Distillation in Medical Image Segmentation

model-releasesarxiv-cs-cv

arXiv:2609.13271v1 Announce Type: new Abstract: Medical image segmentation needs diverse training data, but hospitals hold complementary scans they cannot share for privacy and regulatory reasons. Kno

Agents

Carbon-Aware Routing for Function Calling in Edge-Cloud LLM Systems

arXiv:2609.13559v1 Announce Type: new Abstract: Large Language Models (LLMs) with function-calling capabilities are becoming critical for modern agentic AI systems. Nevertheless, current deployments t

agentsarxiv-cs-ai

CatchMonitor: a machine learning system for automated fish discard quantification

model-releasesarxiv-cs-cv

arXiv:2609.15484v1 Announce Type: new Abstract: We report on the continued development of CatchMonitor, resulting in a prototype computer vision system designed to automatically quantify discarded fis

Causal Analysis and Mitigation of Spurious Onsets in Full-Duplex Speech LLMs

arXiv:2609.13445v1 Announce Type: new Abstract: Speech-to-speech LLMs like Moshi, and its derivative PersonaPlex, can listen and speak concurrently through full-duplex generation. However, they can be

researcharxiv-cs-cl

Certifiably Interpretable Training of ReLU-MLPs for Boolean Tasks with Guaranteed Truth-Table Generalization

arXiv:2609.13439v1 Announce Type: cross Abstract: As compute scales, models evolve, and training algorithms advance, our ability to explain the increasingly powerful AI systems they enable is eroding.

Applications

CGGT: Curve-Grounded Geometry Transformer for 3D Parametric Curve Reconstruction

arXiv:2609.14521v1 Announce Type: new Abstract: Recovering editable 3D parametric curves from 2D images is a fundamental challenge in computer graphics, bridging pixel-based perception and vector-base

applicationsarxiv-cs-cv

CLIMATEAGENT: Multi-Agent Orchestration for Complex Climate Data Science Workflows

arXiv:2511.20109v2 Announce Type: replace Abstract: Climate science demands automated workflows to transform comprehensive questions into data-driven statements across massive, heterogeneous datasets.

Convergence rates for generative drifting flows: fixed-scale obstructions and multihead acceleration

arXiv:2609.15193v1 Announce Type: new Abstract: Drifting models offer a promising route to faster generative AI: they perform gradual transport during training, while generating new samples in a singl

researcharxiv-cs-lg

CyFM: Cylindrical Optimal Transport for Few-Step Complex-Valued Flow Matching

arXiv:2609.14171v1 Announce Type: new Abstract: Complex-valued signals, such as Magnetic Resonance Imaging (MRI) and audio spectrograms, are almost always modelled as flat two-channel Euclidean data.

researcharxiv-cs-lg

Data Attribution at Scale via Influence Matrix Estimation

arXiv:2609.15044v1 Announce Type: cross Abstract: Data attribution seeks to quantify how individual training examples shape a model's predictions and underpins problems including data valuation, machi

researcharxiv-cs-lg

Decentralized Multi-Robot Task Allocation Under Degraded Communication: A Benchmark of Performance, Reliability, and Computation

model-releasesarxiv-cs-ro

arXiv:2609.13711v1 Announce Type: new Abstract: Selecting a decentralized Multi-Robot Task Allocation (MRTA) method for embedded deployment on autonomous platforms requires considering more than route

Differential Privacy of Gaussian Process Posterior Sampling

arXiv:2606.17995v2 Announce Type: replace-cross Abstract: We study the privacy of releasing functional posterior sample paths from a Gaussian process (GP) when the entire training set including covari

Diffusion-Based Generation of Gait Trajectories

arXiv:2609.14642v1 Announce Type: new Abstract: Generation of musculoskeletal gait trajectories conditioned on patient-specific parameters remains a key challenge for wearable robotics and rehabilitat

DiTAR+: Dual Optimization for Robust Autoregressive Diffusion Speech Synthesis

arXiv:2609.13909v1 Announce Type: cross Abstract: Continuous-latent Autoregressive Diffusion Transformer (AR-DiT) models have demonstrated immense potential in zero-shot speech generation. However, th

safetyarxiv-cs-ai

Agents

Do Not Restart: Residual Completion for Stateful Agent Handoffs

arXiv:2609.13800v1 Announce Type: new Abstract: Routing and cascades reduce tool-agent cost by transferring control across models, but stateful handoffs must preserve accepted choices, realized effect

agentsarxiv-cs-ai