Search: “models”

arXiv:2607.02234v1 Announce Type: new Abstract: On-policy self-distillation (OPSD) has emerged as a promising paradigm for improving LLM reasoning, where a privileged teacher with access to reference

arXiv:2511.17089v2 Announce Type: replace-cross Abstract: We present Spanning Tree Autoregressive (STAR) modeling, which can incorporate prior knowledge of images, such as center bias and locality, to

arXiv:2607.02469v1 Announce Type: cross Abstract: Software tests and code evolve together: a code change should be followed by new or updated tests that record the new software behavior. Yet existing

arXiv:2607.02322v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models have shown remarkable promise in generalized robotic manipulation. However, their spatial generalization remains fra

arXiv:2607.02371v1 Announce Type: cross Abstract: Over 285 million people worldwide live with a visual impairment, for whom everyday tasks such as avoiding obstacles, locating personal belongings, rec

arXiv:2607.01145v1 Announce Type: new Abstract: Data analysis in the medical domain often encounters scenarios involving a limited target dataset and a large, unannotated dataset with a general distri

arXiv:2604.00767v2 Announce Type: replace Abstract: Wearable human activity recognition (HAR) has made steady progress, yet much of this progress remains grounded in fixed-window, closed-set classific

arXiv:2607.00509v1 Announce Type: new Abstract: Positron emission tomography (PET) provides essential functional information for disease assessment, however reducing injected activity or acquisition t

arXiv:2607.00726v1 Announce Type: new Abstract: Audio-visual feature extraction is a fundamental component of multimodal understanding and generation tasks. However, existing evaluation protocols for

arXiv:2607.00297v1 Announce Type: cross Abstract: When LLM agents use evaluator feedback to adapt their behavior in closed loops, evaluator biases propagate through the agent's strategy distribution -

arXiv:2507.02961v2 Announce Type: replace-cross Abstract: Modern transportation network modeling increasingly involves the integration of diverse methodologies including sensor-based forecasting, rein

arXiv:2603.26661v2 Announce Type: replace Abstract: Most recent advances in 3D generative modeling rely on diffusion or flow-matching formulations. We instead explore a fully autoregressive alternativ

arXiv:2603.16943v2 Announce Type: replace-cross Abstract: Skeleton-based action recognition is widely applied in sensor-based systems, including human-computer interaction and intelligent surveillance

arXiv:2607.01205v1 Announce Type: new Abstract: We present Linkify, a framework for learning from interface-augmented assembly graphs to enable context-aware part retrieval in mechanical assemblies. W

Reinforcement learning (RL) finetuning has become a key technique for enhancing large language models (LLMs) on reasoning-intensive tasks, motivating its extension to vision language models (VLMs). Wh

arXiv:2603.08279v2 Announce Type: replace Abstract: Accurate 3D reconstruction of vertebral anatomy from ultrasound is important for guiding minimally invasive spine interventions, but it remains chal

arXiv:2607.00190v1 Announce Type: cross Abstract: Recent advances in reinforcement learning have produced superhuman agents across a wide range of competitive games. As a byproduct, researchers have b

arXiv:2606.19096v2 Announce Type: replace Abstract: European Portuguese (pt-PT) is largely absent from OCR benchmarks, which skew toward high-resource languages. The few benchmarks that cover pt-PT fo

arXiv:2607.00834v1 Announce Type: new Abstract: Near-Infrared (NIR) spectroscopy has emerged as a promising alternative to traditional soil analysis methods, offering advantages such as speed, low cos

arXiv:2606.13148v2 Announce Type: replace Abstract: Climate and environmental decision-making increasingly requires reasoning across heterogeneous inputs, including gridded physical data, satellite im

arXiv:2602.14679v2 Announce Type: replace Abstract: Diffusion model advances have enabled powerful text-guided image editing, but also raise ethical and legal risks such as deepfakes and unauthorized

This paper presents V1, a framework that unifies text generation with self-verification mechanisms to enable parallel reasoning processes in language models. The approach allows models to generate mul

arXiv:2606.31137v1 Announce Type: new Abstract: This paper proposes a Bayesian filtering-based approach for learning the dynamics of a physical system from partial, noisy measurements. We model the sy

arXiv:2602.10528v2 Announce Type: replace-cross Abstract: We propose a novel swap-adversarial framework that mitigates high inter-subject variability and the high-dimensional low-sample-size problem i

arXiv:2606.30970v1 Announce Type: new Abstract: Autonomous AI agents increasingly perform consequential actions on behalf of human principals, including financial transactions, external communications

arXiv:2606.30863v1 Announce Type: new Abstract: Agents typically assume an expert user -- one with well-formed preferences about what they want -- and default to clarifying questions whenever the task

arXiv:2606.31169v1 Announce Type: new Abstract: Existing AI-assisted oracle bone inscription (OBI) visual recognition and understanding studies mainly focus on character-level, ignoring the long-form

arXiv:2606.31326v1 Announce Type: new Abstract: Recently, unified image generation and understanding have been extensively explored. However, extending such unified modeling paradigms to the video dom

arXiv:2606.30919v1 Announce Type: cross Abstract: Edge-cloud inference collaborations are often designed with a routing estimator that decides whether to offload each frame from weak models at the edg

arXiv:2606.31508v1 Announce Type: new Abstract: Automatic speech recognition for children's reading remains underdeveloped for most African languages, including Bambara, despite its potential value fo

arXiv:2606.13239v2 Announce Type: replace-cross Abstract: Existing computer-use agents remain fundamentally limited in professional software manipulation: GUI-based agents suffer from fragile visual g

arXiv:2606.31449v1 Announce Type: new Abstract: We investigate the contextual slate bandit problem with generalized linear rewards under limited adaptivity. At each round, the learner is presented wit

arXiv:2606.31007v1 Announce Type: new Abstract: Vision foundation models such as SAM 3 can provide transferable object-level structure across diverse surgical video conditions, but segmentation output

arXiv:2512.21002v3 Announce Type: replace-cross Abstract: Distilling the capabilities from a large reasoning model (LRM) to a smaller student model often involves training on substantial amounts of re

arXiv:2511.11046v3 Announce Type: replace-cross Abstract: Graph neural networks (GNNs) have become an indispensable tool for analyzing relational data. Classical GNNs are broadly classified into three

arXiv:2602.06625v2 Announce Type: replace Abstract: Existing LLM-as-a-Judge systems suffer from three fundamental limitations: limited adaptivity to task- and domain-specific evaluation criteria, syst

'For agents within an actual product, I have gravitated to using LangChain DeepAgents. I feel like their base harness is less heavy, and their abstraction for building agents that use skills and tools

arXiv:2606.32039v1 Announce Type: new Abstract: Visual generative models are typically trained in two stages. A tokenizer is first trained for reconstruction and then frozen, after which a generator i

arXiv:2606.31179v1 Announce Type: new Abstract: As AI agents become increasingly capable of complex, long-horizon reasoning, rigorous and holistic evaluation is essential for measuring progress toward

arXiv:2606.31496v1 Announce Type: new Abstract: In recent years, most research on multimodal salient object detection (SOD) and camouflaged object detection (COD) typically aims to improve performance

arXiv:2606.30790v1 Announce Type: cross Abstract: Romanized Code Mixing (RCM), where bilingual speakers fluidly blend local languages with English in Roman script, has emerged as the dominant form of

arXiv:2509.10406v4 Announce Type: replace Abstract: Pretraining transformers on long sequences (entire code repositories, collections of related documents) is bottlenecked by quadratic attention costs

My prediction: the excitement for Fable 5 will wear off really fast. Reposting this to help those who will be extremely disappointed after they play with Fable 5 and run out of tokens or can't do much

Nano Banana 2 Lite is a text-to-image model optimized for efficiency and speed, likely designed for use within the ComfyUI node-based interface. This lightweight version of the model enables users to

arXiv:2510.17917v2 Announce Type: replace-cross Abstract: Data unlearning aims to remove the influence of specific training samples from a trained model. In fine-tuning methods, data unlearning relies

arXiv:2606.30673v1 Announce Type: cross Abstract: Autoregressive Transformers dominate high-quality mesh generation by producing artist-worthy topologies, yet their inherent sequential decoding induce