Search: “models”

Neural Network Optimization Reimagined: Decoupled Techniques for Scratch and Fine-Tuning

arXiv:2604.22838v1 Announce Type: cross Abstract: With the accumulation of resources in the era of big data and the rise of pre-trained models in deep learning, optimizing neural networks for various

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'Noisier' Noise Contrastive Eestimation is (Almost) Maximum Likelihood

DGX agent

arXiv:2405.16730v2 Announce Type: replace-cross Abstract: Noise Contrastive Estimation (NCE) has fueled major breakthroughs in representation learning and generative modeling. Yet a long-standing chal

researcharxiv-cs-ai

28 Apr 2026

ODE-GS: Latent ODEs for Dynamic Scene Extrapolation with 3D Gaussian Splatting

arXiv:2506.05480v4 Announce Type: replace-cross Abstract: We introduce ODE-GS, a novel approach that integrates 3D Gaussian Splatting with latent neural ordinary differential equations (ODEs) to enabl

One Size Fits None: Heuristic Collapse in LLM Investment Advice

arXiv:2604.23837v1 Announce Type: new Abstract: Large language models are increasingly deployed as advisors in high-stakes domains -- answering medical questions, interpreting legal documents, recomme

applicationsarxiv-cs-cl

OptProver: Bridging Olympiad and Optimization through Continual Training in Formal Theorem Proving

arXiv:2604.23712v1 Announce Type: cross Abstract: Recent advances in formal theorem proving have focused on Olympiad-level mathematics, leaving undergraduate domains largely unexplored. Optimization,

ParkingScenes: A Structured Dataset for End-to-End Autonomous Parking in Simulation Scenes

arXiv:2604.22835v1 Announce Type: cross Abstract: Autonomous parking remains a critical yet challenging task in intelligent driving systems, particularly within constrained urban environments where ma

Preserving Long-Tailed Expert Information in Mixture-of-Experts Tuning

arXiv:2604.23036v1 Announce Type: cross Abstract: Despite MoE models leading many benchmarks, supervised fine-tuning (SFT) for the MoE architectures remains difficult because its router layers are fra

safetyarxiv-cs-cl

PushupBench: Your VLM is not good at counting pushups

arXiv:2604.23407v1 Announce Type: cross Abstract: Large vision-language models (VLMs) can recognize extit{what} happens in video but fail to count extit{how many} times. We introduce extbf{PushupBench

QEVA: A Reference-Free Evaluation Metric for Narrative Video Summarization with Multimodal Question Answering

arXiv:2604.24052v1 Announce Type: cross Abstract: Video-to-text summarization remains underexplored in terms of comprehensive evaluation methods. Traditional n-gram overlap-based metrics and recent la

RAS: a Reliability Oriented Metric for Automatic Speech Recognition

arXiv:2604.24278v1 Announce Type: cross Abstract: Automatic speech recognition systems often produce confident yet incorrect transcriptions under noisy or ambiguous conditions, which can be misleading

Reclaiming Residual Knowledge: A Novel Paradigm to Low-Bit Quantization

arXiv:2408.00923v2 Announce Type: replace-cross Abstract: This paper explores a novel paradigm in low-bit (i.e. 4-bits or lower) quantization, differing from existing state-of-the-art methods, by fram

ResAF-Net: An Anchor-Free Attention-Based Network for Tree Detection and Agricultural Mapping in Palestine

arXiv:2604.23653v1 Announce Type: cross Abstract: Reliable agricultural data is essential for food security, land-use planning, and economic resilience, yet in Palestine, such data remains difficult t

Resolution scaling governs DINOv3 transfer performance in chest radiograph classification

arXiv:2510.07191v3 Announce Type: replace-cross Abstract: Self-supervised learning (SSL) has improved visual representation learning, but its value in chest radiography remains uncertain. DINOv3 exten

Revisiting On-Policy Distillation: Empirical Failure Modes and Simple Fixes

arXiv:2603.25562v2 Announce Type: replace-cross Abstract: On-policy distillation (OPD) is increasingly used in LLM post-training because it can leverage a teacher model to provide dense supervision on

safetyarxiv-cs-ai

S2G-RAG: Structured Sufficiency and Gap Judging for Iterative Retrieval-Augmented QA

arXiv:2604.23783v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) grounds language models in external evidence, but multi-hop question answering remains difficult because iterativ

SceneSelect: Selective Learning for Trajectory Scene Classification and Expert Scheduling

arXiv:2604.24514v1 Announce Type: new Abstract: Accurate trajectory prediction is fundamentally challenging due to high scene heterogeneity - the severe variance in motion velocity, spatial density, a

safetyarxiv-cs-lg

Self-Supervised Learning for Android Malware Detection on a Time-Stamped Dataset

arXiv:2604.23025v1 Announce Type: cross Abstract: Android malware detectors built with machine learning often suffer from temporal bias: models are trained and evaluated without respecting apps' actua

safetyarxiv-cs-lg

SolarTformer: A Transformer Based Deep Learning Approach for Short Term Solar Power Forecasting

arXiv:2604.24306v1 Announce Type: cross Abstract: Accurate forecasting of solar power output is essential for efficient integration of renewable energy into the grid. In this study, an attention-based

Spatiotemporal Degradation-Aware 3D Gaussian Splatting for Realistic Underwater Scene Reconstruction

arXiv:2604.23551v1 Announce Type: new Abstract: Reconstructing realistic underwater scenes from underwater video remains a meaningful yet challenging task in the multimedia domain. The inherent spatio

SPLIT: Separating Physical-Contact via Latent Arithmetic in Image-Based Tactile Sensors

arXiv:2604.24449v1 Announce Type: cross Abstract: Training machine learning models for robotic tactile sensing requires vast amounts of data, yet obtaining realistic interaction data remains a challen

Stochastic KV Routing: Enabling Adaptive Depth-Wise Cache Sharing

arXiv:2604.22782v1 Announce Type: cross Abstract: Serving transformer language models with high throughput requires caching Key-Values (KVs) to avoid redundant computation during autoregressive genera

Agents

SwarmDrive: Semantic V2V Coordination for Latency-Constrained Cooperative Autonomous Driving

arXiv:2604.22852v1 Announce Type: cross Abstract: Cloud-hosted LLM inference for autonomous driving adds round-trip delay and depends on stable connectivity, while purely local edge models struggle un

agentsarxiv-cs-ai

TACO: Efficient Communication Compression of Intermediate Tensors for Scalable Tensor-Parallel LLM Training

arXiv:2604.24088v1 Announce Type: cross Abstract: Handling communication overhead in large-scale tensor-parallel training remains a critical challenge due to the dense, near-zero distributions of inte

The Override Gap: A Magnitude Account of Knowledge Conflict Failure in Hypernetwork-Based Instant LLM Adaptation

arXiv:2604.23750v1 Announce Type: cross Abstract: Hypernetwork-based methods such as Doc-to-LoRA internalize a document into an LLM's weights in a single forward pass, but they fail systematically on

The Spectral Lifecycle of Transformer Training: Transient Compression Waves, Persistent Spectral Gradients, and the Q/K--V Asymmetry

arXiv:2604.22778v1 Announce Type: cross Abstract: We present the first systematic study of weight matrix singular value spectra during transformer pretraining, tracking full SVD decompositions of ever

TOL: Textual Localization with OpenStreetMap

arXiv:2604.01644v2 Announce Type: replace Abstract: Natural language provides an intuitive way to express spatial intent in geospatial applications. While existing localization methods often rely on d

Towards Continual Expansion of Data Coverage: Automatic Text-guided Edge-case Synthesis

arXiv:2509.26158v2 Announce Type: replace-cross Abstract: The performance of deep neural networks is strongly influenced by the quality of their training data. However, mitigating dataset bias by manu

Towards High-Fidelity CAD Generation via LLM-Driven Program Generation and Text-Based B-Rep Primitive Grounding

arXiv:2603.11831v2 Announce Type: replace Abstract: The field of Computer-Aided Design (CAD) generation has made significant progress in recent years. Existing methods typically fall into two separate

applicationsarxiv-cs-cv

Transferable Physical-World Adversarial Patches Against Object Detection in Autonomous Driving

arXiv:2604.23105v1 Announce Type: new Abstract: Deep learning drives major advances in autonomous driving (AD), where object detectors are central to perception. However, adversarial attacks pose sign

safetyarxiv-cs-cv

Understanding the Limits of Automated Evaluation for Code Review Bots in Practice

arXiv:2604.24525v1 Announce Type: cross Abstract: Automated code review (ACR) bots are increasingly used in industrial software development to assist developers during pull request (PR) review. As ado

What Understanding Means in AI-Laden Astronomy

arXiv:2601.10038v2 Announce Type: replace-cross Abstract: Artificial intelligence is rapidly transforming astronomical research, yet the scientific community has largely treated this transformation as

applicationsarxiv-cs-ai

'Yeah, my OpenClaw runs entirely on talkie-1930-13b-base, I connect to it only through telegram. No, not that telegram.'

applicationsethan-mollick--x

This post describes a personal AI setup called 'OpenClaw' that runs on the talkie-1930-13b-base model and is accessed via a custom Telegram interface, with the author humorously clarifying this is not

An Interdisciplinary and Cross-Task Review on Missing Data Imputation

arXiv:2511.01196v3 Announce Type: replace-cross Abstract: Missing data is a fundamental challenge in data science, significantly hindering analysis and decision-making across a wide range of disciplin

applicationsarxiv-cs-ai

ArmSSL: Adversarial Robust Black-Box Watermarking for Self-Supervised Learning Pre-trained Encoders

arXiv:2604.22550v1 Announce Type: cross Abstract: Self-supervised learning (SSL) encoders are invaluable intellectual property (IP). However, no existing SSL watermarking for IP protection can concurr

Asymmetric Goal Drift in Coding Agents Under Value Conflict

arXiv:2603.03456v2 Announce Type: replace Abstract: Coding agents are increasingly deployed autonomously, at scale, and over long-context horizons. To be effective and safe, these agents must navigate

BLAST: Benchmarking LLMs with ASP-based Structured Testing

arXiv:2604.22306v1 Announce Type: cross Abstract: Large Language Models (LLMs) have demonstrated remarkable performance across a broad spectrum of tasks, including natural language understanding, dial

Calibrated Principal Component Regression

arXiv:2510.19020v2 Announce Type: replace-cross Abstract: We propose a new method for statistical inference in generalized linear models. In the overparameterized regime, Principal Component Regressio

safetyarxiv-cs-lg

Characterizing pitch and roll torque coupling in insect-sized flapping-wing robots using a microfabricated gimbal

arXiv:2604.22121v1 Announce Type: cross Abstract: Sub-gram flapping-wing flying insect robots (FIRs) are challenging to model because of mechanical complexity in their wings, unsteady aerodynamic flow

researcharxiv-cs-ro

Closed Form Relations and Higher-Order Approximations of First and Second Derivatives of the Tangent Operator on SE(3)

arXiv:2604.22287v1 Announce Type: cross Abstract: The Lie group SE(3) of isometric orientation preserving transformation is used for modeling multibody systems, robots, and Cosserat continua. The use

researcharxiv-cs-ro

Cross-Domain Offshore Wind Power Forecasting: Transfer Learning Through Meteorological Clusters

arXiv:2601.19674v2 Announce Type: replace-cross Abstract: Ambitious decarbonisation targets are rapidly increasing the commission of new offshore wind farms. For these newly commissioned plants to run

Different Strokes for Different Folks: Writer Identification for Historical Arabic Manuscripts

arXiv:2604.22515v1 Announce Type: new Abstract: Handwritten Arabic manuscripts preserve the Arab world's intellectual and cultural heritage, and writer identification supports provenance, authenticity

Distance-Misaligned Training in Graph Transformers and Adaptive Graph-Aware Control

arXiv:2604.22413v1 Announce Type: cross Abstract: Graph Transformers can mix information globally, but this flexibility also creates failure modes: some tasks require long-range communication while ot

EgoMAGIC- An Egocentric Video Field Medicine Dataset for Training Perception Algorithms

arXiv:2604.22036v1 Announce Type: cross Abstract: This paper introduces EgoMAGIC (Medical Assistance, Guidance, Instruction, and Correction), an egocentric medical activity dataset collected as part o

How attention simplifies mental representations for planning

arXiv:2506.09520v2 Announce Type: replace-cross Abstract: Human planning is efficient--it frugally deploys limited cognitive resources to accomplish difficult tasks--and flexible--adapting to novel pr

KuaiLive: A Real-time Interactive Dataset for Live Streaming Recommendation

arXiv:2508.05633v2 Announce Type: replace-cross Abstract: Live streaming platforms have become a dominant form of online content consumption, offering dynamically evolving content, real-time interacti

LATMiX: Learnable Affine Transformations for Microscaling Quantization of LLMs

arXiv:2602.17681v2 Announce Type: replace-cross Abstract: Post-training quantization (PTQ) is a widely used approach for reducing the memory and compute costs of large language models (LLMs). Recent s

researcharxiv-cs-cl

Long-tail Internet photo reconstruction

arXiv:2604.22714v1 Announce Type: new Abstract: Internet photo collections exhibit an extremely long-tailed distribution: a few famous landmarks are densely photographed and easily reconstructed in 3D

NeuronMLP: Efficient LLM Inference via Singular Value Decomposition Compression and Tiling on AWS Trainium

arXiv:2510.25977v4 Announce Type: replace Abstract: Emerging AI accelerators have started to gain attention and offer new opportunities for efficient inference of large language models (LLMs). Trainiu

researcharxiv-cs-cl