Search: “model-releases”

SAM 2++: Tracking Anything at Any Granularity

arXiv:2510.18822v4 Announce Type: replace Abstract: Due to the varying granularity of target states across different tasks, most existing trackers are tailored to a single task, which specificity limi

SAME: A Semantically-Aligned Music Autoencoder

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arXiv:2605.18613v1 Announce Type: cross Abstract: Latent representations are at the heart of the majority of modern generative models. In the audio domain they are typically produced by a neural-audio

model-releasesarxiv-cs-ai

19 May 2026

Scalable Knowledge Editing for Mixture-of-Experts LLMs via Tensor-Structured Updates

arXiv:2605.16686v1 Announce Type: new Abstract: Knowledge editing (KE) provides a lightweight alternative to repeated fine-tuning of LLMs. However, most existing KE methods target dense feed-forward l

Scale-Equivariant Generative Forecasting: Weight-Tied Dilated Convolutions, Wavelet Scattering Inputs, and Spectral-Consistency Training for Self-Similar Time Series

arXiv:2605.17582v1 Announce Type: new Abstract: Many natural and engineered time series -- equity returns, climate anomalies, turbulent velocities, neural recordings, packet-level network traffic -- a

Scales++: Compute Efficient Evaluation Subset Selection with Cognitive Scales Embeddings

arXiv:2510.26384v2 Announce Type: replace Abstract: The prohibitive cost of evaluating large language models (LLMs) on comprehensive benchmarks necessitates the creation of small yet representative da

Scaling Laws for Code: A More Data-Hungry Regime

arXiv:2510.08702v2 Announce Type: replace Abstract: Code Large Language Models (LLMs) are revolutionizing software engineering. However, scaling laws that guide the efficient training are predominantl

SCARED-C: Corrected Camera Poses for Endoscopic Depth Estimation

arXiv:2605.16628v1 Announce Type: new Abstract: The SCARED dataset is a widely used benchmark for endoscopic depth estimation, offering ground-truth 3D reconstructions captured with a structured light

Scheduling That Speaks: An Interpretable Programmatic Reinforcement Learning Framework

arXiv:2605.18454v1 Announce Type: cross Abstract: Deep reinforcement learning (DRL) has recently emerged as a promising approach to solve combinatorial optimization problems such as job shop schedulin

SCICONVBENCH: Benchmarking LLMs on Multi-Turn Clarification for Task Formulation in Computational Science

arXiv:2605.18630v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly deployed as scientific AI as- sistants, and a growing body of benchmarks evaluates their capabilities acro

SE-GA: Memory-Augmented Self-Evolution for GUI Agents

arXiv:2605.16883v1 Announce Type: new Abstract: Autonomous Graphical User Interface (GUI) agents often struggle with multi-step tasks due to constrained context windows and static policies that fail t

SEDD: Scalable and Efficient Dataset Deduplication with GPUs

arXiv:2501.01046v4 Announce Type: replace Abstract: Dataset deduplication is widely recognized as a crucial preprocessing step that enhances data quality and improves the performance of large language

Seeing Together:Multi-Robot Cooperative Egocentric Spatial Reasoning with Multimodal Large Language Models

arXiv:2605.18431v1 Announce Type: new Abstract: Multimodal Large Language Models (MLLMs) have made substantial progress in egocentric video understanding, but their ability to reason cooperatively fro

Self-Improving CAD Generation Agents with Finite Element Analysis as Feedback

arXiv:2605.17448v1 Announce Type: cross Abstract: Computer-aided design (CAD) is the backbone of modern industrial design, yet learned CAD generators still fall short of real engineering pipelines: th

Self-Play Only Evolves When Self-Synthetic Pipeline Ensures Learnable Information Gain

arXiv:2603.02218v2 Announce Type: replace-cross Abstract: Large language models (LLMs) make it plausible to build systems that improve through self-evolving loops, but many existing proposals are bett

Self-supervised Hierarchical Visual Reasoning with World Model

arXiv:2605.17537v1 Announce Type: new Abstract: 3D open-world environments with adversarial opponents remain a core challenge for reinforcement learning due to their vast state spaces. Effective reaso

Self-Supervised On-Policy Distillation for Reasoning Language Models

arXiv:2605.17497v1 Announce Type: new Abstract: GRPO-style RLVR trains reasoning models from multiple on-policy attempts per prompt, but typically uses these attempts only through terminal rewards. We

Setting the Stage: Text-Driven Scene-Consistent Image Generation

arXiv:2512.12598v3 Announce Type: replace Abstract: We focus on the foundational task of Scene Staging: given a reference scene image and a text condition specifying an actor category to be generated

Shallow ReLU^s Networks in L^p-Type and Sobolev Spaces: Approximation and Path-Norm Controlled Generalization

arXiv:2605.18468v1 Announce Type: cross Abstract: We study approximation by shallow ReLU^s networks, sigma_s(t)=max{0,t}^s, and the generalization behavior of such networks under ell_1 path-norm contr

ShareChat: A Dataset of Chatbot Conversations in the Wild

arXiv:2512.17843v4 Announce Type: replace-cross Abstract: By evaluating Large Language Models (LLMs) through uniform, text-only interfaces, current academic benchmarks obscure how the unique designs a

SIPO: Stabilized and Improved Preference Optimization for Aligning Diffusion Models

arXiv:2505.21893v3 Announce Type: replace-cross Abstract: Preference learning has garnered extensive attention as an effective technique for aligning diffusion models with human preferences in visual

SIREM: Speech-Informed MRI Reconstruction with Learned Sampling

arXiv:2605.18221v1 Announce Type: cross Abstract: Real-time magnetic resonance imaging (rtMRI) of speech production enables non-invasive visualization of dynamic vocal-tract motion and is valuable for

SkillGenBench: Benchmarking Skill Generation Pipelines for LLM Agents

arXiv:2605.18693v1 Announce Type: new Abstract: As LLM agents are increasingly built around reusable skills, a central challenge is no longer only whether agents can use provided skills, but whether t

Skills on the Fly: Test-Time Adaptive Skill Synthesis for LLM Agents

arXiv:2605.16986v1 Announce Type: cross Abstract: LLM agents benefit from reusable skills, yet test-time tasks often require guidance more specific than a static skill library can provide. We propose

SkillsVote: Lifecycle Governance of Agent Skills from Collection, Recommendation to Evolution

arXiv:2605.18401v1 Announce Type: cross Abstract: Long-horizon LLM agents leave traces that could become reusable experience, but raw trajectories are noisy and hard to govern. We treat Agent Skills a

SkyNative: A Native Multimodal Framework for Remote Sensing Visual Evidence Reasoning

arXiv:2605.17949v1 Announce Type: new Abstract: Remote sensing vision-language models commonly rely on pretrained visual encoders to convert images into semantic features before language-model reasoni

SLEIGHT-Bench: A Benchmark of Evasion Attacks Against Agent Monitors

arXiv:2605.16626v1 Announce Type: cross Abstract: Since autonomous coding agents generate complex behaviors at high-volume, we may want to use other LLMs to monitor actions to reduce the risk from dan

Small-scale photonic Kolmogorov-Arnold networks using standard telecom nonlinear modules

arXiv:2604.08432v2 Announce Type: replace-cross Abstract: Photonic neural networks promise ultrafast inference, yet most architectures rely on linear optical meshes with electronic nonlinearities, rei

SocialMemBench: Are AI Memory Systems Ready for Social Group Settings?

arXiv:2605.17789v1 Announce Type: cross Abstract: Memory systems for AI assistants were built for single-user dialogue and fail characteristically when applied to multi-party social group settings. Th

SomaliWeb v1: A Quality-Filtered Somali Web Corpus with a Matched Tokenizer and a Public Language-Identification Benchmark

arXiv:2605.18232v1 Announce Type: cross Abstract: Somali is a Cushitic language of the Horn of Africa with ~25 million speakers, yet no documented dedicated Somali pretraining corpus with a companion

Sometin Beta Pass Notin (SBPN): Improving Multilingual ASR for Nigerian Languages via Knowledge Distillation

arXiv:2605.17710v1 Announce Type: new Abstract: Although modern multilingual Automatic Speech Recognition (ASR) systems support several Nigerian languages, their performance consistently lags behind h

Sparse Training of Neural Networks based on Multilevel Mirror Descent

arXiv:2602.03535v2 Announce Type: replace Abstract: We introduce a dynamic sparse training algorithm based on linearized Bregman iterations / mirror descent that exploits the naturally incurred sparsi

SPATIOROUTE: Dynamic Prompt Routing for Zero-Shot Spatial Reasoning

arXiv:2605.18209v1 Announce Type: cross Abstract: Spatial question answering over egocentric video is a challenging task that requires Vision-Language Models (VLMs) to reason about 3D object positions

SpecSem-Net: Integrating Spectral and Semantic Features for Robust AI-generated Video Detection

arXiv:2605.17311v1 Announce Type: new Abstract: The remarkable visual fidelity of recent commercial video generative models, such as Sora and Veo, renders robust AI-generated video detection increasin

Spherical VAE with Cluster-Aware Feasible Regions: Guaranteed Prevention of Posterior Collapse

arXiv:2603.10935v4 Announce Type: replace-cross Abstract: Variational autoencoders (VAEs) frequently suffer from posterior collapse, where the latent variables become uninformative as the approximate

Stabilizing, Scaling & Enhancing MeanFlow for Large-scale Diffusion Distillation

arXiv:2605.17834v1 Announce Type: new Abstract: Diffusion models exhibit remarkable generative capability, but their high latency limits practical deployment. Many studies have attempted to reduce sam

StableVLA: Towards Robust Vision-Language-Action Models without Extra Data

arXiv:2605.18287v1 Announce Type: new Abstract: It is infeasible to encompass all possible disturbances within the training dataset. This raises a critical question regarding the robustness of Vision-

State-of-the-Art Claims Require State-of-the-Art Evidence

arXiv:2605.17273v1 Announce Type: cross Abstract: State-of-the-Art (SOTA) claims pervade Artificial Intelligence (AI) and Machine Learning (ML) research. These claims rest on benchmark evaluations, wh

Statistical Limits and Efficient Algorithms for Differentially Private Federated Learning

arXiv:2605.18656v1 Announce Type: cross Abstract: Federated Learning is a leading framework for training ML and AI models collaboratively across numerous user devices or databases. We study the trade-

SteadyDancer: Harmonized and Coherent Human Image Animation with First-Frame Preservation

arXiv:2511.19320v2 Announce Type: replace Abstract: Preserving first-frame identity while ensuring precise motion control is a fundamental challenge in human image animation. The Image-to-Motion Bindi

Strategic Over-Parameterization for Generalizable Low-Rank Adaptation

arXiv:2605.16470v1 Announce Type: cross Abstract: Adapting large language models (LLMs) to downstream tasks via full fine-tuning is increasingly impractical due to its computational and memory demands

StreamPro: From Reactive Perception to Proactive Decision-Making in Streaming Video

arXiv:2605.16381v1 Announce Type: cross Abstract: Proactive streaming video understanding requires models to continuously process video streams and decide when to respond, rather than merely what to r

StrLoRA: Towards Streaming Continual Visual Instruction Tuning for MLLMs

arXiv:2605.16353v1 Announce Type: cross Abstract: Continual Visual Instruction Tuning (CVIT) enables Multimodal Large Language Models to incrementally acquire new abilities. However, existing CVIT met

Structured Labeling Enables Faster Vision-Language Models for End-to-End Autonomous Driving

arXiv:2506.05442v2 Announce Type: replace-cross Abstract: Vision-Language Models (VLMs) offer a promising approach to end-to-end autonomous driving due to their human-like reasoning capabilities. Howe

Structured Neural Marked Point Processes for Interpretable Event Interaction Modeling

arXiv:2605.17568v1 Announce Type: new Abstract: Multi-class event streams arise in numerous real-world applications, where uncovering structured, interpretable inter-event relationships, together with

STT-Arena: A More Realistic Environment for Tool-Using with Spatio-Temporal Dynamics

arXiv:2605.18548v1 Announce Type: cross Abstract: Large language models (LLMs) deployed in real-world agentic applications must be capable of replanning and adapting when mid-task disruptions invalida

StyleText: A Large-Scale Dataset and Benchmark for Stylized Scene Text Inpainting

arXiv:2605.17309v1 Announce Type: cross Abstract: We present StyleText, a large-scale dataset and benchmark for localized scene-text inpainting with style preservation. StyleText contains 28,518 image

Supervise Less, See More: Training-free Nuclear Instance Segmentation with Prototype-Guided Prompting

arXiv:2511.19953v2 Announce Type: replace Abstract: Accurate nuclear instance segmentation is a pivotal task in computational pathology, supporting data-driven clinical insights and facilitating downs

Supervising the search process produces reliable and generalizable information-seeking agents

arXiv:2502.13957v3 Announce Type: replace-cross Abstract: Large language models (LLMs) are transforming web search by shifting from document ranking to synthesizing answers, and are increasingly deplo