Search: “model-releases”

Importance-Guided Basis Selection for Low-Rank Decomposition of Large Language Models

arXiv:2605.01627v1 Announce Type: new Abstract: Low-rank decomposition is a compelling approach for compressing large language models, but its effectiveness hinges on selecting which singular-vector b

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Model Releases

InfantAgent-Next: A Multimodal Generalist Agent for Automated Computer Interaction

DGX agent

arXiv:2505.10887v3 Announce Type: replace Abstract: This paper introduces extsc{InfantAgent-Next}, a generalist agent capable of interacting with computers in a multimodal manner, encompassing text, i

model-releasesarxiv-cs-ai

5 May 2026

Instance-Aware Parameter Configuration in Bilevel Late Acceptance Hill Climbing for the Electric Capacitated Vehicle Routing Problem

arXiv:2605.00572v1 Announce Type: new Abstract: Algorithm performance in combinatorial optimization is highly sensitive to parameter settings, while a single globally tuned configuration often fails t

InstructMoLE: Instruction-Guided Mixture of Low-rank Experts for Multi-Conditional Image Generation

arXiv:2512.21788v3 Announce Type: replace Abstract: Parameter-Efficient Fine-Tuning of Diffusion Transformers (DiTs) for diverse, multi-conditional tasks often suffers from task interference when usin

Interactive Multi-Turn Retrieval for Health Videos

arXiv:2605.01409v1 Announce Type: cross Abstract: The growing availability of health-related instructional videos creates new opportunities for clinical training, patient rehabilitation, and health ed

InterPhys: Physics-aware Human Motion Synthesis in a Dynamic Scene

arXiv:2605.01036v1 Announce Type: new Abstract: This paper tackles the problem of physics-aware human motion synthesis in a dynamic scene. Unlike existing works which mainly tend to generate physicall

Interpretable experiential learning based on state history and global feedback

arXiv:2605.00940v1 Announce Type: new Abstract: A new interpretable experiential learning model based on state history and global feedback is presented. It is capable of learning a behavioral model re

Is there 'Secret Sauce'' in Large Language Model Development?

arXiv:2602.07238v2 Announce Type: replace-cross Abstract: Do leading LLM developers possess a proprietary ``secret sauce'', or is LLM performance driven by scaling up compute? Using training and bench

jina-vlm: Small Multilingual Vision Language Model

arXiv:2512.04032v3 Announce Type: replace Abstract: We present jina-vlm, a token-efficient 2.4B parameter vision-language model that achieves state-of-the-art multilingual VQA performance among open 2

Joint Architecture-Token-Bitwidth Multi-Axis Optimization of Vision Transformers for Semiconductor IC Packaging

arXiv:2605.01742v1 Announce Type: new Abstract: Vision Transformers (ViTs) have achieved strong performance in visual recognition, yet their deployment in resource-constrained industrial environments

LabBuilder: Protocol-Grounded 3D Layout Generation for Interactable and Safe Laboratory

arXiv:2605.02288v1 Announce Type: new Abstract: Automated laboratories hold the promise of accelerating scientific discovery, yet their deployment is bottlenecked by the difficulty of designing safe a

Language models recognize dropout and Gaussian noise applied to their activations

arXiv:2604.17465v2 Announce Type: replace Abstract: We provide evidence that language models can detect, localize and, to a certain degree, verbalize the difference between perturbations applied to th

Latent Trajectory Dynamics in Large Language Models: A Manifold Evolution Framework with Empirical Validation

arXiv:2505.20340v3 Announce Type: replace Abstract: Understanding how latent representations evolve during generation is a central open problem in large language model interpretability. We introduce e

LatentDiff: Scaling Semantic Dataset Comparison to Millions of Images

arXiv:2605.00899v1 Announce Type: new Abstract: We present LatentDiff, a scalable framework for semantic dataset comparison that operates directly in the latent space of pretrained vision encoders. By

Learning in the Fisher Subspace: A Guided Initialization for LoRA Fine-Tuning

arXiv:2605.01046v1 Announce Type: new Abstract: LoRA adapts large language models (LLMs) by restricting updates to low-rank subspaces of pre-trained weights. While this substantially reduces training

Leveraging Imperfect Medical Data: A Manifold-Consistent Spatio-Temporal Network for Sensor-based Human Activity Recognition

arXiv:2605.00913v1 Announce Type: new Abstract: Sensor-based Human Activity Recognition (HAR) has attracted increasing attention in medical and healthcare monitoring, particularly with the growth of I

Linear-Time Global Visual Modeling without Explicit Attention

arXiv:2605.01711v1 Announce Type: new Abstract: Existing research largely attributes the global sequence modeling capability of Transformers to the explicit computation of attention weights, a process

LiteVLA-H: Dual-Rate Vision-Language-Action Inference for Onboard Aerial Guidance and Semantic Perception

arXiv:2605.00884v1 Announce Type: new Abstract: Vision-language-action (VLA) models have shown strong semantic grounding and task generalization in manipulation, but aerial deployment remains difficul

LittleBit-2: Maximizing the Spectral Energy Gain in Sub-1-Bit LLMs via Latent Geometry Alignment

arXiv:2603.00042v2 Announce Type: replace Abstract: We identify the Spectral Energy Gain in extreme model compression, where low-rank binary approximations outperform tiny-rank floating-point baseline

LLM-Foraging: Large Language Models for Decentralized Swarm Robot Foraging

model-releasesarxiv-cs-ro

arXiv:2605.01461v1 Announce Type: new Abstract: Swarm foraging algorithms, such as the central-place foraging algorithm (CPFA), typically rely on offline parameter optimization using genetic algorithm

LUMINA: A Grid Foundation Model for Benchmarking AC Optimal Power Flow Surrogate Learning

arXiv:2605.02133v1 Announce Type: new Abstract: AC optimal power flow (ACOPF) is foundational yet computationally expensive in power grid operations, driving learning-based surrogates for large-scale

Mamoda2.5: Enhancing Unified Multimodal Model with DiT-MoE

arXiv:2605.02641v1 Announce Type: new Abstract: We present Mamoda2.5, a unified AR-Diffusion framework that seamlessly integrates multimodal understanding and generation within a single architecture.

mdok-style at SemEval-2026 Task 9: Finetuning LLMs for Multilingual Polarization Detection

arXiv:2605.02695v1 Announce Type: new Abstract: SemEval-2026 Task 9 is focused on multilingual polarization detection. Specifically, it covers the identification of multilingual, multicultural and mul

Mean-Field Path-Integral Diffusion: From Samples to Interacting Agents

arXiv:2605.00007v1 Announce Type: cross Abstract: Independent sample generation is the prevailing paradigm in modern diffusion-based generative models of AI. We ask a different question: can samples c

Medmarks: A Comprehensive Open-Source LLM Benchmark Suite for Medical Tasks

arXiv:2605.01417v1 Announce Type: new Abstract: Evaluating large language models (LLMs) for medical applications remains challenging due to benchmark saturation, limited data accessibility, and insuff

MedMosaic: A Challenging Large Scale Benchmark of Diverse Medical Audio

arXiv:2605.00969v1 Announce Type: cross Abstract: We present MedMosaic, a medical audio question-answering dataset designed to benchmark language and audio reasoning models under realistic clinical co

Meta-learning Structure-Preserving Dynamics

arXiv:2508.11205v2 Announce Type: replace Abstract: Structure-preserving approaches to dynamics discovery have demonstrated great potential for modeling physical systems due to their use of strong ind

Metric Unreliability in Multimodal Machine Unlearning: A Systematic Analysis and Principled Unified Score

arXiv:2605.02206v1 Announce Type: new Abstract: Machine unlearning in Vision-Language Models (VLMs) is required for compliance with the General Data Protection Regulation (GDPR), yet current evaluatio

Mextsuperscript{4}Fuse: Lightweight State-Space MoE with a Cross-Scale Gating Bridge for Brain Tumor Segmentation

arXiv:2605.02444v1 Announce Type: new Abstract: Encoder-decoder imbalance and the reliance on large input volumes make many 3D brain tumor segmentation models both compute-heavy and brittle. We presen

Minimal, Local, Causal Explanations for Jailbreak Success in Large Language Models

arXiv:2605.00123v1 Announce Type: new Abstract: Safety trained large language models (LLMs) can often be induced to answer harmful requests through jailbreak prompts. Because we lack a robust understa

Minimum Specification Perturbation: Robustness as Distance-to-Falsification in Causal Inference

arXiv:2605.01579v1 Announce Type: cross Abstract: Empirical causal claims depend on many analyst decisions, from selecting covariates to choosing estimators. Existing robustness tools summarize how re

Model-Dowser: Data-Free Importance Probing to Mitigate Catastrophic Forgetting in Multimodal Large Language Models

arXiv:2602.04509v4 Announce Type: replace Abstract: Fine-tuning Multimodal Large Language Models (MLLMs) on task-specific data is an effective way to improve performance on downstream applications. Ho

Model Merging: Foundations and Algorithms

arXiv:2605.01580v1 Announce Type: new Abstract: Modern deep learning usually treats models as separate artifacts: trained independently, specialized for particular purposes, and replaced when improved

MOGO: Residual Quantized Hierarchical Causal Transformer for High-Quality and Real-Time 3D Human Motion Generation

arXiv:2506.05952v4 Announce Type: replace Abstract: Recent advances in transformer-based text-to-motion generation have led to impressive progress in synthesizing high-quality human motion. Neverthele

Molecular Representations for Large Language Models

arXiv:2605.01822v1 Announce Type: new Abstract: Large Language Models (LLMs) are increasingly being used to support scientific discovery. In chemistry, tasks such as reaction prediction and structure

MolmoAct2: Action Reasoning Models for Real-world Deployment

model-releasesarxiv-cs-ro

arXiv:2605.02881v1 Announce Type: new Abstract: Vision-Language-Action (VLA) models aim to provide a single generalist controller for robots, but today's systems fall short on the criteria that matter

MolViBench: Evaluating LLMs on Molecular Vibe Coding

arXiv:2605.02351v1 Announce Type: new Abstract: Molecular Vibe Coding, a paradigm where chemists interact with LLMs to generate executable programs for molecular tasks, has emerged as a flexible alter

MorphIt: Flexible Spherical Approximation of Robot Morphology for Representation-driven Adaptation

model-releasesarxiv-cs-ro

arXiv:2507.14061v2 Announce Type: replace Abstract: What if a robot could rethink its own morphological representation to better meet the demands of diverse tasks? Most robotic systems today treat the

MOSAIC: Multi-agent Orchestration for Task-Intelligent Scientific Coding

arXiv:2510.08804v3 Announce Type: replace Abstract: We present MOSAIC, a multi-agent Large Language Model (LLM) framework for solving challenging scientific coding tasks. Unlike general-purpose coding

MPCS: Neuroplastic Continual Learning via Multi-Component Plasticity and Topology-Aware EWC

arXiv:2605.02509v1 Announce Type: new Abstract: Continual learning systems face a fundamental tension between plasticity -- acquiring new knowledge -- and stability -- retaining prior knowledge. We in

Multi-fidelity surrogates for mechanics of composites: from co-kriging to multi-fidelity neural networks

arXiv:2605.02871v1 Announce Type: cross Abstract: Composite materials exhibit strongly hierarchical and anisotropic properties governed by coupled mechanisms spanning constituents, plies, laminates, s

Multi-Perspective Transformers in ARC-AGI-2 Challenge

arXiv:2605.01154v1 Announce Type: new Abstract: ARC-AGI-2 is a benchmark of human-intuitive visual puzzles that measures a machine's ability to generalize from limited examples, interpret symbolic mea

MultiBreak: A Scalable and Diverse Multi-turn Jailbreak Benchmark for Evaluating LLM Safety

arXiv:2605.01687v1 Announce Type: new Abstract: We present MultiBreak, a scalable and diverse multi-turn jailbreak benchmark to evaluate large language model (LLM) safety. Multi-turn jailbreaks mimic

Multiple Choice Questions: Reasoning Makes Large Language Models (LLMs) More Self-Confident, Especially When They are Wrong

arXiv:2501.09775v3 Announce Type: replace Abstract: Multiple Choice Question (MCQ) tests are among the most used methods for evaluating large language models (LLMs). Besides checking the correctness o

NAKUL-Med: Spectral-Graph State Space Models with Dynamics Kernels for Medical Signals

arXiv:2605.00871v1 Announce Type: cross Abstract: State space models (SSMs) achieve linear-time complexity but struggle with multi-channel physiological signals due to three limitations: fixed kernels

Neighbor2Inverse: Self-Supervised Denoising for Low-Dose Region-of-Interest Phase Contrast CT

arXiv:2605.01075v1 Announce Type: new Abstract: Propagation-based X-ray phase-contrast imaging (PBI) enables high-contrast visualization of lung structures and holds strong medical potential. However,

Object-Level Explanations for Image Geolocation Models: a GeoGuessr use-case

arXiv:2605.00912v1 Announce Type: new Abstract: When humans play geolocation games such as GeoGuessr, they rely on concrete visual cues, such as road markings, vegetation, or architectural details, to

OceanPile: A Large-Scale Multimodal Ocean Corpus for Foundation Models

arXiv:2605.00877v1 Announce Type: cross Abstract: The vast and underexplored ocean plays a critical role in regulating global climate and supporting marine biodiversity, yet artificial intelligence ha