Search: “model-releases”

Dive into the Scene: Breaking the Perceptual Bottleneck in Vision-Language Decision Making via Focus Plan Generation

arXiv:2606.04046v1 Announce Type: cross Abstract: In embodied vision-language decision making tasks such as robotic manipulation and navigation, Vision-Language and Vision-Language-Action Models (VLMs

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Model Releases

DLLG: Dynamic Logit-Level Gating of LLM Experts

DGX agent

arXiv:2606.04378v1 Announce Type: new Abstract: Leveraging multiple specialized LLMs can combine complementary strengths, but existing approaches trade adaptability for stability: routing commits prem

model-releasesarxiv-cs-cl

4 Jun 2026

DLO-Lab: Benchmarking Deformable Linear Object Manipulations with Differentiable Physics

model-releasesarxiv-cs-ro

arXiv:2606.04206v1 Announce Type: new Abstract: We address the challenge of enabling robots to manipulate deformable linear objects (DLOs), such as ropes, cables, and rubber bands. Prior work has prim

DMAConv: Dual Mask-Adaptive Convolution for Remote Sensing Pansharpening

arXiv:2512.08331v2 Announce Type: replace Abstract: Pansharpening aims to fuse a high-resolution panchromatic image with a low-resolution multispectral image. Existing deep learning methods, including

dMX: Differentiable Mixed-Precision Assignment for Low-Precision Floating-Point Formats

arXiv:2606.04115v1 Announce Type: cross Abstract: Quantizing large language models (LLMs) to low-precision floating-point representations is central to efficient deployment, yet applying a single bit-

Do Transformers Need Three Projections? Systematic Study of QKV Variants

arXiv:2606.04032v1 Announce Type: cross Abstract: Transformers have become the standard solution for various AI tasks, with the query, key, and value (QKV) attention formulation playing a central role

Dream.exe: Can Video Generation Models Dream Executable Robot Manipulation?

arXiv:2606.04811v1 Announce Type: new Abstract: Video generation models have made impressive strides in synthesizing visually compelling content, yet their outputs remain confined to the virtual domai

Ekka: Automated Diagnosis of Silent Errors in LLM Inference

arXiv:2606.04594v1 Announce Type: cross Abstract: LLM serving frameworks are quickly evolving with a complex software stack and a vast number of optimizations. The rapid development process can introd

Emotion Entanglement and Bayesian Inference for Multi-Dimensional Emotion Understanding

arXiv:2604.00819v2 Announce Type: replace-cross Abstract: Understanding emotions in natural language is inherently a multi-dimensional reasoning problem, where multiple affective signals interact thro

Evaluating Large Language Models in Dynamic Clinical Decision-Making with Standardized Patient Cases

arXiv:2606.05112v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly proposed as clinical agents, yet static, single-turn benchmarks cannot capture how a model dynamically del

Evaluating Zero-Shot and One-Shot Adaptation of Small Language Models in Leader-Follower Interaction

arXiv:2602.23312v3 Announce Type: replace-cross Abstract: Leader-follower interaction is an important paradigm in human-robot interaction (HRI). Yet, assigning roles in real time remains challenging f

EvoPrompt: Guided Prompt Evolution for Vision-Language Models Adaptation

arXiv:2603.09493v2 Announce Type: replace-cross Abstract: The adaptation of large-scale vision-language models (VLMs) to downstream tasks with limited labeled data remains a significant challenge. Whi

Exploring the Topology and Memory of Consensus: How LLM Agents Agree, Fragment, or Settle When Forming Conventions

arXiv:2606.04197v1 Announce Type: cross Abstract: How much should an LLM agent remember, and how should multi-agent systems be connected when trying to reach consensus? We show these two design choice

Exposing Blindspots: Cultural Bias Evaluation in Generative Image Models

arXiv:2510.20042v3 Announce Type: replace Abstract: Generative image models produce striking visuals yet often misrepresent culture. Prior work has examined cultural bias mainly in text-to-image (T2I)

FindIt: A Format-Informed Visual Detection Benchmark for Generalist Multimodal LLMs

arXiv:2606.04282v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are predominantly evaluated on free-form vision-language tasks such as visual question answering, captioning, a

FinTradeBench: A Financial Reasoning Benchmark for LLMs

arXiv:2603.19225v3 Announce Type: replace-cross Abstract: Real-world financial decision-making is a challenging problem that requires reasoning over heterogeneous signals, including company fundamenta

Flow Matching Calibration for Simulation-Based Inference under Model Misspecification

arXiv:2509.23385v5 Announce Type: replace-cross Abstract: Simulation-based inference (SBI) is transforming experimental sciences by enabling parameter estimation in complex non-linear models from simu

Food-R1: A Unified Multi-Task Food Vision-Language Model with Reinforcement Learning

arXiv:2606.04986v1 Announce Type: new Abstract: Recent studies have explored Vision-Language Models (VLMs) for food analysis. However, most existing methods rely primarily on supervised fine-tuning (S

From Symbolic to Geometric: Enabling Spatial Reasoning in Large Language Models

arXiv:2606.04381v1 Announce Type: cross Abstract: Recent large language models (LLMs) often appear to exhibit spatial reasoning ability; however, this capability is largely symbolic, arising from patt

From Untrusted Input to Trusted Memory: A Systematic Study of Memory Poisoning Attacks in LLM Agents

arXiv:2606.04329v1 Announce Type: cross Abstract: Memory is a core component of AI agents, enabling them to accumulate knowledge across interactions and improve performance. However, persistent memory

GeM-NR: Geometry-Aware Multi-View Editing for Nonrigid Scene Changes

arXiv:2606.05142v1 Announce Type: cross Abstract: Recent developments in multi-view image editing with generative models have brought us a step closer toward general 3D content generation and customiz

GENEB: Why Genomic Models Are Hard to Compare

arXiv:2606.04525v1 Announce Type: new Abstract: Progress in genomic foundation models is difficult to assess due to fragmented benchmarks, incompatible evaluation protocols, and task-specific reportin

Geometry-Aware Hallucination Detection in Large Language Models

arXiv:2601.06196v3 Announce Type: replace-cross Abstract: Large language models (LLMs) frequently generate factually incorrect or unsupported content, commonly referred to as hallucinations. Prior wor

Geometry Gaussians: Decoupling Appearance and Geometry in Gaussian Splatting

arXiv:2606.05124v1 Announce Type: cross Abstract: After the success of 3D Gaussian Splatting (3DGS) for novel view synthesis, many works have explored how to also use it for geometric surface represen

Geometry-Preserving Unsupervised Alignment for Heterogeneous Foundation Models

arXiv:2606.04385v1 Announce Type: new Abstract: Foundation models have driven rapid progress in computer vision, yet the two dominant paradigms, vision-language foundation models (VLMs) and vision-onl

Gradient estimators for parameter inference in discrete stochastic kinetic models

arXiv:2604.02121v2 Announce Type: replace-cross Abstract: Stochastic kinetic models are ubiquitous in physics, yet inferring their parameters from experimental data remains challenging. For determinis

Graph Set Transformer

arXiv:2606.05116v1 Announce Type: new Abstract: We introduce the Graph Set Transformer (GST), a neural network architecture for learning on sets of graphs, designed for tasks in which per-element pred

Gravity-Aware Hierarchical Routing for Lightweight SensorLLM on Human Activity Recognition

arXiv:2606.04019v1 Announce Type: cross Abstract: Recent studies on sensor-language alignment have shown that two-stage frameworks can improve the semantic modeling ability of wearable-sensor human ac

GroupToM-Bench: Benchmarking Group Theory of Mind and Nonlinear Social Emergence in MLLMs

arXiv:2606.04184v1 Announce Type: new Abstract: True general intelligence requires not only a model of the physical world but also a social world model: the capacity to infer how individual mental sta

HD-DinoMoE: A Class-Aware Hierarchical Dual Mixture-of-Experts Network for Scleral Anomaly Segmentation in Complex Acquisition Scenarios

arXiv:2606.04888v1 Announce Type: new Abstract: Traditional Chinese Medicine (TCM) ocular inspection provides empirical cues for assessing scleral surface anomalies, but its clinical use remains subje

Hierarchical Self-Supervised Adversarial Training for Robust Vision Models in Histopathology

arXiv:2503.10629v2 Announce Type: replace Abstract: Adversarial attacks pose significant challenges for vision models in critical fields like healthcare, where reliability is essential. Although adver

High-Quality Entity Segmentation and Grounding

arXiv:2402.02555v2 Announce Type: replace-cross Abstract: In this work, we propose ESG, a pipeline for high-quality entity segmentation and grounding supported by a new dataset EntitySeg. At first, th

HighTide: An Agent-Curated Open-Source VLSI Benchmark Suite

arXiv:2606.04126v1 Announce Type: cross Abstract: We introduce HighTide, an evolving AI-assisted benchmark suite. Specifically, the contributions are: (i) a diverse open-source suite spanning multiple

HORIZON: Recoverability-Governed Curriculum for Physical-Domain Scaling

model-releasesarxiv-cs-ro

arXiv:2606.05143v1 Announce Type: new Abstract: Scaling robust robot policies requires more than broader randomization, because physical-domain experience must remain organized and learnable throughou

Hyper-ICL: Attention Calibration with Hyperbolic Anchor Distillation for Multimodal In-Context Learning

arXiv:2606.04434v1 Announce Type: new Abstract: Multimodal In-Context Learning (ICL) has emerged as a practical inference paradigm for Multimodal Large Language Models, where a small set of interleave

Identifying and Correcting Label Noise for Robust GNNs via Influence Contradiction

arXiv:2601.17469v2 Announce Type: replace Abstract: Graph Neural Networks (GNNs) have shown remarkable capabilities in learning from graph-structured data with various applications such as social anal

Imagine Before You Draw: Visual Prompt Engineering for Image Generation

arXiv:2606.04457v1 Announce Type: new Abstract: Incorporating visual semantic representations as an intermediate step before image generation can reduce the modeling difficulty between text and images

Impostor: An Agent-Curated Benchmark for Realistic AIGC Manipulation Localization

arXiv:2606.04545v1 Announce Type: new Abstract: Recent advances in generative image editing have improved the realism and controllability of localized image manipulation, raising new challenges for im

InstantRetouch: Efficient and High-Fidelity Instruction-Guided Image Retouching with Bilateral Space

arXiv:2606.05071v1 Announce Type: new Abstract: Language-guided photo retouching aims to adjust color and tone while preserving geometry and texture. Recently, diffusion-based retouching shows a super

Interfaze: The Future of AI is built on Task-Specific Small Models

arXiv:2602.04101v2 Announce Type: replace Abstract: We present Interfaze, a native hybrid model that fuses task-specific deep neural networks (CNNs and DNNs) directly into a transformer decoder throug

Invariant Gradient Alignment for Robust Reasoning Distillation

arXiv:2606.05025v1 Announce Type: cross Abstract: Large language models (LLMs) suffer from shortcut learning: they systematically fail on out-of-distribution (OOD) inputs whose semantic surface differ

It's TIME: Towards the Next Generation of Time Series Forecasting Benchmarks

arXiv:2602.12147v4 Announce Type: replace Abstract: Time series foundation models (TSFMs) are revolutionizing the forecasting landscape from specific dataset modeling to generalizable task evaluation.

Knowledge Index of Noah's Ark

arXiv:2606.05104v1 Announce Type: new Abstract: Knowledge benchmarks for LLMs face three issues: scaling-driven designs that do not operationalize disciplinary representativeness; flat-payment annotat

LCSHBench: A Multilingual, Consensus-Grounded Benchmark for Library of Congress Subject Heading Assignment

arXiv:2606.04382v1 Announce Type: cross Abstract: Automated subject cataloging assigns controlledvocabulary headings to bibliographic records, but LCSH has no standard public benchmark. We introduce L

LDA-1B: Scaling Latent Dynamics Action Model via Universal Embodied Data Ingestion

model-releasesarxiv-cs-ro

arXiv:2602.12215v2 Announce Type: replace Abstract: Recent robot foundation models largely rely on large-scale behavior cloning, which imitates expert actions but discards transferable dynamics knowle

LDARNet: DNA Adaptive Representation Network with Learnable Tokenization for Genomic Modeling

arXiv:2606.04552v1 Announce Type: new Abstract: Genomic foundation models increasingly adopt large language model architectures, yet almost universally rely on fixed tokenization schemes such as k-mer

Learning Long Range Spatio-Temporal Representations over Continuous Time Dynamic Graphs with State Space Models

arXiv:2606.04672v1 Announce Type: cross Abstract: Continuous-time dynamic graphs (CTDGs) provide a richer framework to capture fine-grained temporal patterns in evolving relational data. Long-range in

Learning When to Act or Refuse: Guarding Agentic Reasoning Models for Safe Multi-Step Tool Use

arXiv:2603.03205v2 Announce Type: replace Abstract: Agentic language models operate in a fundamentally different safety regime than chat models: they must plan, call tools, and execute long-horizon ac