Search: “model-releases”

Efficient Test-time Adaptation through Candidate Verification and Divergence Shifts

arXiv:2610.06147v1 Announce Type: new Abstract: Vision-language models (VLMs) achieve strong zero-shot transferability but remain vulnerable to target-domain shifts at inference time. Test-time adapta

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Model Releases

EfficientXpert: Efficient Domain Adaptation for Large Language Models via Propagation-Aware Pruning

DGX agent

arXiv:2511.19935v3 Announce Type: replace Abstract: Deploying domain-specialized large language models on resource-constrained hardware motivates reducing both adaptation cost and the number of retain

model-releasesarxiv-cs-lg

6 Oct 2026

EgoExo-Next:Benchmarking Vision-Language Models on Visual-Option Next-State and Cross-View Reasoning

arXiv:2610.04506v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly evaluated for egocentric and cross-view video reasoning, yet existing benchmarks largely focus on semanti

EMBER-Bench: Benchmarking Cross-Event Causal Memory in Long-Horizon Embodied Tasks

arXiv:2610.05013v1 Announce Type: new Abstract: Lifelong physical agents must reason over extended interactions where past events continue to shape the world long after they disappear from view. Beyon

EMG-FM-Bench: A Comprehensive Benchmark for Foundation Model Transfer and Adaptation on Electromyography

arXiv:2610.06450v1 Announce Type: new Abstract: Foundation models (FMs) are increasingly being developed for general time series and physiological signals, yet their transferability to downstream phys

Enhancing Long-Video VLM Embeddings with Query-Aware Streaming Latent Reasoning

arXiv:2610.04864v1 Announce Type: new Abstract: Long-video embedding requires capturing sparse query-relevant evidence under a limited visual-token budget. Uniform sampling can miss brief events in vi

Environmental sensor readings in two crop disease image datasets identify the session in which each image was taken

arXiv:2610.06369v1 Announce Type: new Abstract: Integrating environmental sensor data with leaf imagery is widely reported to boost crop disease classification accuracy. In this work, we reveal that t

EORestore-Agent: Fidelity-Guided Agentic Restoration of Remote Sensing Images with Composite Degradations

arXiv:2610.06196v1 Announce Type: new Abstract: Remote sensing images often carry composite degradations, in which haze, cloud, noise, blur, low light, and low resolution coexist. Restoring them requi

Errors of LLM-Assisted Literature Retrieval in Environmental Science: A Comparison Study of Abstract versus Full-text Based Prompts

arXiv:2610.05690v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used for literature search and synthesis. However, it is unclear whether they retrieve accurate bibliogr

Every View Counts: View-Consistent Panoptic Quality for Multi-view Panoptic Segmentation

arXiv:2610.05911v1 Announce Type: new Abstract: Multi-view panoptic segmentation assigns a semantic class and a scene-level instance ID to every pixel of an unordered set of images, and recent feed-fo

EvoMem-VLA: State-Evolution Memory for Long-Horizon Robot Manipulation

arXiv:2610.05418v1 Announce Type: cross Abstract: Most vision-language-action (VLA) models rely on current observations and lose task-relevant evidence once it leaves view, limiting performance on lon

EvoState: Closed-Loop Visual State Management for Long-Form Video Generation

arXiv:2606.16184v2 Announce Type: replace Abstract: Multi-shot long-form video generation remains challenging due to identity drift and compounding inconsistencies across shots. Existing methods encod

EXHIB: A Benchmark for Realistic and Diverse Evaluation of Function Similarity in the Wild

arXiv:2604.01554v2 Announce Type: replace-cross Abstract: Binary Function Similarity Detection (BFSD) is a core problem in software security, supporting tasks such as vulnerability analysis, malware c

Expanding LLM Reasoning

arXiv:2610.05584v1 Announce Type: new Abstract: Extra inference compute is usually spent on sampling more reasoning chains. We study where inside an existing chain an additional continuation should be

Exploiting Hierarchical Controller Structure in Contextual Parameter Learning for Humanoid Loco-Manipulation

arXiv:2610.04609v1 Announce Type: cross Abstract: Hierarchical control architectures are widely used to decompose complex control problems into interacting control levels and are particularly importan

Extending Dynamic World Surface Water Mapping to Sentinel-1 with AlphaEarth Embeddings

arXiv:2610.06704v1 Announce Type: new Abstract: Dynamic World (DW) maps land use and land cover globally at 10 m from Sentinel-2 (S2) imagery, but only for cloud-free observations, which limits where

FACET: Factorized Asymmetric Conditioning for Efficient Transport in High-Fidelity Fluorescence Microscopy Synthesis

arXiv:2610.05353v1 Announce Type: cross Abstract: Fluorescence microscopy reveals where proteins localize, but only a limited number of proteins can be imaged in the same cell; generating these images

FADE: Frame-Aware Diffusion-Transformer-based Multi-Concept Erasure for Video Unlearning

arXiv:2610.03980v1 Announce Type: new Abstract: Text-to-video (T2V) diffusion models can reproduce copyrighted, violent, or explicit content, which motivates concept erasure: removing designated conce

FairRSFM: A Biome-Aware Benchmark and Debiasing Framework for Remote Sensing Foundation Models

arXiv:2610.05790v1 Announce Type: new Abstract: Remote sensing foundation models (RSFMs) are commonly evaluated using aggregate metrics, which can hide systematic performance disparities across ecolog

Feature identification for parameter extraction and defect detection using machine learning

arXiv:2610.05812v1 Announce Type: new Abstract: Process control of advanced semiconductor nodes is not only pushing the limits of metrology equipment requirements in terms of resolution and throughput

Fitting Vision Adapters at Frontier Scales

arXiv:2610.05897v1 Announce Type: new Abstract: Training a small projector between a frozen vision encoder and language model is an established approach to multimodal learning. As the parameter count

FLAT: Smoothing the Rugged Landscape for Learnable, Sample-Efficient Traffic Calibration

arXiv:2610.04337v1 Announce Type: cross Abstract: Calibrating microscopic traffic models for digital twins is an expensive black-box optimization problem: tuning car-following and lane-changing parame

FOCUS: Fine-Grained Open-Vocabulary Change Detection for Uncertainty-Aware Semi-Static Scenes

model-releasesarxiv-cs-ro

arXiv:2610.05639v1 Announce Type: new Abstract: Autonomous robots operating over long periods must keep their environmental memory up to date as the world changes between visits. In semi-static enviro

From Sight to Foresight: Predictive Spatial Reasoning in Vision-Language Models

arXiv:2610.04139v1 Announce Type: new Abstract: Predicting future spatial states supports collision avoidance and timely decision-making in dynamic environments. However, existing vision-language mode

From Transformation to Target State: Rethinking Query Representation for Zero-Shot Composed Image Retrieval

arXiv:2610.05993v1 Announce Type: new Abstract: Composed image retrieval (CIR) aims to retrieve a desired target image from a query consisting of a reference image and a modification text. This task e

Frozen in a Frame: The Velocity Blind Spot in JEPA World Models

arXiv:2610.04585v1 Announce Type: new Abstract: Joint-embedding predictive architectures (JEPAs) for world modeling train an encoder so a predictor maps a current embedding and action to the next fram

FTD-GNO: Memory-Efficient Graph Neural Operators through Functional Tensor Decomposition of the Kernel

arXiv:2610.04212v1 Announce Type: new Abstract: Graph Neural Operators (GNOs) provide flexible surrogate models for learning solution operators of partial differential equations (PDEs). However, stand

Gated Graph Neural Networks for Learning Hidden Independent Cascade Dynamics

arXiv:2610.04033v1 Announce Type: cross Abstract: Information and infectious diseases spread through social networks, but the spreading probabilities driving them are hard to estimate without per-node

Gaussian Flow Dynamics: Simulation-Free Neural SDE Learning Beyond One-Time Marginals

arXiv:2610.04390v1 Announce Type: cross Abstract: Simulation-free training of latent Stochastic Differential Equations (SDEs) relies on a variational posterior process whose one-time marginals are tra

Gaussian Universality and Its Breakdown in Tensor-Network Machine Learning

arXiv:2610.06080v1 Announce Type: cross Abstract: Gaussian-process limits are powerful in describing overparameterized machine learning models, yet their validity in structured tensor-network architec

Gefen: Optimized Stochastic Optimizer

arXiv:2606.13894v3 Announce Type: replace-cross Abstract: AdamW is a default optimizer for deep learning, but its moment states add two parameter-sized buffers to training memory, increasing the cost

Geometry-Dependent Approximation for Non-Monotone k-Submodular Maximization

arXiv:2610.04049v1 Announce Type: cross Abstract: We study nonnegative, non-monotone k-submodular maximization with kge2 labels under support constraints, and show how the certified approximation coef

GitSwarm: Decentralized Compounding Inference

arXiv:2610.04862v1 Announce Type: cross Abstract: Long-horizon problem solving and scientific research require computation to accumulate across successive attempts. Partial solutions, experimental fin

GNN-CB: A Graph Neural Network Competition Benchmark for Human and LLM Evaluation

arXiv:2610.05387v1 Announce Type: new Abstract: Large language models (LLMs) have demonstrated strong performance on coding and reasoning benchmarks; however, their ability to solve graph-structured m

GPU-Accelerated Bregman Douglas-Rachford Splitting for Discrete Optimal Transport

arXiv:2610.04715v1 Announce Type: cross Abstract: We present GPU-accelerated Bregman Douglas--Rachford splitting algorithm (BDRS) for discrete optimal transport problem in three input formats: an expl

GR-LIO: A Local Ground-Aware LiDAR-Inertial Odometry System Using Body-to-Ground Height

model-releasesarxiv-cs-ro

arXiv:2610.05546v1 Announce Type: new Abstract: LiDAR-inertial odometry (LIO) is widely used for state estimation in ground-based autonomous mobile robots. However, the geometric constraints provided

Graph-Based Floor Separation Using Node Embeddings and Clustering of WiFi Trajectories

arXiv:2505.08088v4 Announce Type: replace-cross Abstract: Vertical localization, particularly floor separation, remains a major challenge in indoor positioning systems operating in GPS-denied multisto

Greedy Multi-Path Block Verification for Faster Decoding in Speculative Sampling

arXiv:2602.16961v2 Announce Type: replace-cross Abstract: The goal of L-step speculative decoding is to accelerate autoregressive decoding of a target model by using a cheaper draft model to generate

Green-Routed Neural Operators: Physics Determines Where the Network Reads

arXiv:2610.05337v1 Announce Type: new Abstract: We identify a mismatch between the physical role of transport fields in many PDEs and their usual role in neural operators: PDEs use them to select read

Grounded in Time: A Multi-Source Dataset and Benchmark for Temporal Grounding in Robotic Manipulation

arXiv:2610.04255v1 Announce Type: cross Abstract: Robotic manipulation often requires inferring task-relevant states from past interactions when the current observation alone is insufficient to determ

GS-Codec: A Gaussian-Splatting Bottleneck for Neural Audio Coding

arXiv:2610.04651v1 Announce Type: cross Abstract: Neural audio codecs compress waveforms into compact discrete tokens that underpin speech language models, real-time communication, and large-scale aud

Hamiltonian Metric Learning and Energy-Based Training: A Dissipative Geometric Framework for Optimization

arXiv:2610.04969v1 Announce Type: new Abstract: Optimization in machine learning is usually expressed through iterative rules that update model parameters using information from the loss landscape. In

Harnessing Multimodal Large Language Models for Training-Free Human-Object Interaction Detection

arXiv:2610.06394v1 Announce Type: new Abstract: Human-object interaction (HOI) detection aims to localize human-object pairs and recognize their interactions. Traditional supervised methods perform st

Homogeneous Semantic Alignment and Hierarchical Expert Routing for Radiology Report Generation

arXiv:2610.04499v1 Announce Type: new Abstract: Radiology report generation (RRG) aims to convert medical images into diagnostic texts to assist in clinical decision-making and alleviate the workload

How Execution Assumptions Change Short-Horizon Sharpe Rankings: Evidence from a Synthetic Trading Benchmark

arXiv:2610.05077v1 Announce Type: new Abstract: Backtests of LLM trading agents often assume that every order fills at the closing price. We ask whether this choice changes only reported returns or al

How RL Reshapes LLM Reasoning: Transferability, Coverage, and Scaling Laws

arXiv:2610.04158v1 Announce Type: new Abstract: Recent studies on reinforcement learning (RL) report seemingly conflicting evidence about large language model (LLM) reasoning. Training on mathematics

Hyperbolic Graph Representation Learning: Embed in One Metric, Optimize with Another

arXiv:2610.06745v1 Announce Type: new Abstract: Hierarchical graphs embed in hyperbolic space with lower distortion than in Euclidean space owing to its negative curvature. However, their gradient-bas

Ideal Paths for Approximating Logistic Gradient Descent Trajectories at Large Initialization

arXiv:2610.04142v1 Announce Type: new Abstract: Modern training on a new task often starts from a previously trained model rather than from scratch, raising the question of how this initialization aff