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From Sentiment Classification to Actionable and Responsible Feedback: A Scoping Review and Evidence Map of NLP in Student Evaluation of Teaching, 2015-2026

arXiv:2609.27939v1 Announce Type: new Abstract: Natural language processing (NLP) applied to open-ended teaching-evaluation comments (Student Evaluation of Teaching, SET) has tracked the field's techn

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Frozen Flows Forget: Diagnosing and Restoring Lost Motion in a Latent-flow World Model

DGX agent

arXiv:2609.28414v1 Announce Type: cross Abstract: Latent world models that integrate a flow in a frozen self supervised latent space train stably and cheaply, yet silently lose the property manipulati

researcharxiv-cs-ai

24 Sept 2026

FSCE: A Target-Aware Frequency-Spatial Collaborative Enhancement Framework for Noise-Resilient SAR ATR

arXiv:2603.21565v2 Announce Type: replace-cross Abstract: Synthetic aperture radar automatic target recognition (SAR ATR) is severely challenged by coherent speckle noise, whose interference can be pr

safetyarxiv-cs-ai

Full-Covariance Smoothing of Bayesian Neural Networks for Online Adaptation

arXiv:2609.27244v1 Announce Type: new Abstract: A neural network's layers can be treated as time steps of a state-space model, turning Bayesian training into a smoothing problem: a forward pass propag

safetyarxiv-cs-lg

Fusion-Aware Direct 3D Gaussian Generation with Structured Patch Latent Flows

arXiv:2609.27779v1 Announce Type: new Abstract: Class-guided 3D object generation is important for intelligent content creation, virtual environments, and digital asset design. Although 3D Gaussian Sp

local-aiarxiv-cs-cv

GaussianDS: Depth-supervised Semantic Gaussian Splatting for Scene Understanding

arXiv:2609.27850v1 Announce Type: new Abstract: 3D Gaussian Splatting provides an efficient representation for 3D reconstruction, and recent extensions attach semantic attributes to Gaussians for open

GaussPDE: Graph-Based Partial Differential Equation-Driven Rendering for 3D Gaussian Splatting

arXiv:2609.27264v1 Announce Type: new Abstract: We present GaussPDE, a framework that injects physically structured partial differential equation (PDE) dynamics into pretrained 3D Gaussian scenes with

Gender Bias in Vision-Language In-Context Learning

arXiv:2609.27682v1 Announce Type: new Abstract: In-context learning (ICL) enables large vision-language models (LVLMs) to perform tasks by following patterns from in-context examples, yet its potentia

Generalizable Robotic Insertion with World Models

arXiv:2609.28258v1 Announce Type: cross Abstract: Robotic assembly in high-mixture settings requires adaptable systems that can handle diverse parts, yet current approaches typically rely on policies

Geometry-anchored PET-aware multimodal pseudo-CT synthesis for whole-body attenuation correction: the BIC-MAC Challenge

arXiv:2609.27848v1 Announce Type: new Abstract: The BIC-MAC challenge targets whole-body pseudo-CT synthesis from NAC-PET, Dixon MRI, and a 2D topogram for CT-less PET attenuation correction. We propo

Geometry-Conditioned Visual Place Recognition in Natural Environments

model-releasesarxiv-cs-ai

arXiv:2609.27370v1 Announce Type: cross Abstract: Visual Place Recognition (VPR) in natural environments remains challenging due to repetitive vegetation, sparse distinctive landmarks, and substantial

GeoRVQ: Decoder-aware geometry for residual-token prediction in physiological signals

arXiv:2609.27018v1 Announce Type: new Abstract: Residual vector quantization (RVQ) turns physiological waveforms into compact token sequences, but conventional masked modeling treats every incorrect t

local-aiarxiv-cs-lg

Geospatial embeddings detect old-growth forests but buffered spatial validation narrows their advantage over Sentinel features

arXiv:2609.28194v1 Announce Type: cross Abstract: Old-growth forests develop over centuries under minimal anthropogenic disturbance, producing structurally complex and biodiverse stands. In Europe, pr

Giving Credit Where It's Due: Redundancy-Aware Learning for Efficient Reasoning

arXiv:2609.27156v1 Announce Type: new Abstract: Large reasoning models can produce correct yet unnecessarily long reasoning traces. Existing methods improve reasoning efficiency with trajectory-level

local-aiarxiv-cs-cl

GLASS: Architecture-Tuned, Composable, Device-Side Linear Algebra for Edge Robotics and Beyond

model-releasesarxiv-cs-ro

arXiv:2609.28179v1 Announce Type: new Abstract: GPU robotics lacks the reusable numerical infrastructure of mature CPU stacks, instead relying on compiler frameworks that introduce overhead or repeate

Tutorials

Global tree forecasters collapse at the hierarchical aggregate: a five-panel failure characterization

arXiv:2609.27912v1 Announce Type: new Abstract: Global forecasting models pool many series and learn one shared function. Gradient-boosted trees are their most common form. We measure a failure of thi

tutorialsarxiv-cs-lg

GLoTouch: Global-to-Local Haptic Perception Using a Parallel Gripper for Object Search, Recognition, and Grasping Without External Vision

arXiv:2609.27695v1 Announce Type: new Abstract: Perceiving objects in the environment is a fundamental capability of autonomous robots. In dark or low-light environments, external cameras often fail t

local-aiarxiv-cs-ro

GLOW: Global Illumination-Aware Inverse Rendering of Indoor Scenes Captured with Dynamic Co-Located Light & Camera

arXiv:2511.22857v2 Announce Type: replace Abstract: Inverse rendering of indoor scenes remains challenging due to the ambiguity between reflectance and lighting, exacerbated by inter-reflections among

GlyRAG: Context-Aware Retrieval-Augmented Framework for Blood Glucose Forecasting

model-releasesarxiv-cs-lg

arXiv:2601.05353v3 Announce Type: replace Abstract: Accurate blood glucose forecasting using continuous glucose monitoring (CGM) data can support the early prediction of dysglycemic risk. However, cur

Godel's and Scott's Variants of the Ontological Argument in Lean 4

arXiv:2609.26806v1 Announce Type: cross Abstract: This paper presents a complete, structure-preserving port to Lean 4 of the Isabelle/HOL dataset accompanying Benzmuller and Scott's study of Godel's m

researcharxiv-cs-ai

Graph Learning with Spectral Connectivity Priors for Scarce Data

arXiv:2609.27278v1 Announce Type: new Abstract: Learning a sparse graph from scarce data is practically important but challenging. Motivated by the desirable combination of local sparsity and strong g

Agents

Gray-Box Model Predictive Control for Articulated Dump Trucks via Gaussian Process Learning of Sideslip

arXiv:2609.27597v1 Announce Type: new Abstract: The growing demand for automation in the mining industry, particularly for the autonomous operation of articulated dump trucks (ADTs), has drawn increas

agentsarxiv-cs-ro

Groundbench: Multi-Resolution Polygon Grounding Exposes the Geometry Gap in Vision-Language Models

model-releasesarxiv-cs-cv

arXiv:2609.27821v1 Announce Type: new Abstract: Bounding-box scores on RefCOCO-family grounding leave little room to distinguish frontier vision-language systems, yet boxes discard object shape. We in

Guides That Cause Actions: An Offline Study of Guide-Action Mutual Reinforcement in Multimodal Web Agents

model-releasesarxiv-cs-cl

arXiv:2609.27353v1 Announce Type: new Abstract: Web agents are usually evaluated in live environments, where environment state and judge models drift between runs, so the same checkpoint rarely reprod

Hard Negatives Reveal What Easy Negatives Hide: Cross-Lingual Harmfulness Representations Degrade with Resource Tier Under Hard Negatives

arXiv:2609.27758v1 Announce Type: cross Abstract: Safety alignment in large language models is trained primarily in English, and recent work reports that the underlying harmfulness representation surv

safetyarxiv-cs-ai

HARN: Hierarchical Associative Resonance Network for Event-Driven Multi-Timeframe Forecasting

arXiv:2609.26822v1 Announce Type: new Abstract: Financial time series evolve across multiple temporal resolutions, challenging forecasting systems to incorporate newly available information without re

Harness as a Language: A Minimalist Agent Framework With Maximal Expressivity

model-releasesarxiv-cs-ai

arXiv:2609.26891v1 Announce Type: new Abstract: Modern language-model agents are built around the extit{agent loop}, where the LLM is placed in an environment exposing a set of tools, and the LLM has

HaRP: High Dynamic Range Photosequencing through Dual Reversed Shutter Scanning

arXiv:2609.28439v1 Announce Type: new Abstract: The adoption of CMOS sensors in mobile photography is frequently compromised by the rolling shutter (RS) effect, which introduces geometric distortions

Hidden not Deleted: How Networks Suppress Entangled Features

arXiv:2609.27593v1 Announce Type: cross Abstract: Concept erasure methods that operate via linear projection assume that features occupy separable subspaces. We show this assumption fails under dense

researcharxiv-cs-ai

High Dynamic Range Video Reconstruction from Single-Exposure Raw Sequences

arXiv:2609.27274v1 Announce Type: new Abstract: Due to the limited dynamic range of conventional image sensors, captured low dynamic range (LDR) video often suffers from highlight clipping and shadow

HINT-Blimp: Human INTent Inference from Multimodal Cues for Robotic Blimps

arXiv:2609.27154v1 Announce Type: new Abstract: In human-robot interaction, traditional interfaces such as joysticks and handheld tablets introduce latency into navigation tasks and require the operat

researcharxiv-cs-ro

HiRE: Hindsight Reward Editing for Policy Finetuning

arXiv:2609.27068v1 Announce Type: new Abstract: Pre-trained robot policies always require finetuning to adapt to specific environments. Reinforcement Learning (RL) offers high performance potential be

safetyarxiv-cs-ro

Honest and Reliable Evaluation and Expert Equivalence Testing of Automated Neonatal Seizure Detection

arXiv:2508.04899v3 Announce Type: replace Abstract: Reliable evaluation of machine learning models for neonatal seizure detection is critical for clinical adoption. Current practices often rely on inc

How Children Design and Reason about Trustworthy AI Chatbots

arXiv:2609.25244v2 Announce Type: replace-cross Abstract: Children increasingly interact with AI chatbots, making trust calibration essential to AI literacy. Prior research has examined children's tru

researcharxiv-cs-ai

How Much Were You Told? Measuring External Information in Peer Reviews

model-releasesarxiv-cs-cl

arXiv:2609.28041v1 Announce Type: new Abstract: Conference policies distinguish using Large Language Models (LLMs) to polish one's own review from delegating the critique, but current Artificial Text

How Sensitive Are LLM Leaderboard Claims to Hidden Model Selection?

arXiv:2609.28177v1 Announce Type: cross Abstract: LLM leaderboard gains can reflect selection among privately evaluated model variants, yet neither the number of variants nor their dependence is publi

Humanoid Locomotion with a Fly-Inspired Recurrent Controller

arXiv:2609.27001v1 Announce Type: new Abstract: We investigate humanoid locomotion with a fly-inspired recurrent controller and identify the pathways supporting its deployed behavior. The controller c

safetyarxiv-cs-ro

Agents

Hunyuan-A13B Technical Report

arXiv:2609.27284v1 Announce Type: new Abstract: We present Hunyuan-A13B, an open-source large language model based on a Mixture-of-Experts architecture. It contains 80 billion total parameters but act

agentsarxiv-cs-ai

Hybrid Gaussians for Robust Open-Vocabulary 3D Segmentation with Multi-View Object Association and Boundary Refinement

arXiv:2609.27462v1 Announce Type: new Abstract: Open-vocabulary 3D segmentation localizes objects from free-form text queries, but remains challenging in real image sequences: incomplete or noisy 2D s

HYDRO: Towards Non-Reversible Face De-Identification Using a High-Fidelity Hybrid Diffusion and Target-Oriented Approach

arXiv:2609.27011v1 Announce Type: new Abstract: Target-oriented face de-identification models aim to anonymize the identity of a target individual across different images or video frames, such that th

hyperbolix: Hyperbolic Deep Learning in JAX

arXiv:2609.28248v1 Announce Type: new Abstract: We present hyperbolix, an open-source library for hyperbolic deep learning in JAX, built on Flax NNX. To our knowledge, it is the first comprehensive, g

I-SplineFlow: Learning Monotone Spline Stochastic Interpolant Schedulers for Few-Step Generation

model-releasesarxiv-cs-lg

arXiv:2609.27963v1 Announce Type: new Abstract: Few-step generation with pretrained diffusion and flow models can be accelerated by lightweight training that optimizes the sampling trajectory rather t

ICM: Intra-class Mixing for Domain Adaptation in Adverse Weather

model-releasesarxiv-cs-cv

arXiv:2609.27533v1 Announce Type: new Abstract: Unsupervised domain adaptation (UDA) for semantic segmentation remains challenging under adverse weather conditions because severe appearance changes en

Image Denoising Using Lower Semi-Frames

arXiv:2609.27893v1 Announce Type: cross Abstract: A blind image denoising framework based on an infinite directional lower semi-frame (DLSF) is proposed for additive white Gaussian noise. The model em

Impact-Time Guidance via Normal Contraction to a Time-to-Go Isochron

arXiv:2609.26906v1 Announce Type: cross Abstract: We develop a contraction-based perspective on impact-time guidance that augments a baseline homing command with a timing bias. The proposed perspectiv

safetyarxiv-cs-ro

Improving Ensemble Filters with Flow Matching

arXiv:2609.28015v1 Announce Type: cross Abstract: Data assimilation estimates a dynamical state from partial and noisy observations. Classical ensemble filters are efficient but restrict analysis upda

local-aiarxiv-cs-lg

Improving LLM-based Autonomous Web Agents with Filtering

model-releasesarxiv-cs-cl

arXiv:2609.27770v1 Announce Type: new Abstract: Autonomous web agents, powered by Large Language Models (LLMs), have garnered significant attention for automating various web-based tasks with multi-st

InfiNoVA: Infinite Novel View Augmentation for Viewpoint Invariant Robot Policies

arXiv:2609.27734v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) policies often rely strongly on the camera viewpoints seen during training, causing substantial performance degradation w

safetyarxiv-cs-ai