Search: “models”

SAMI3D-DW: Interactive Segmentation of Any 3D Medical Images

arXiv:2609.25743v1 Announce Type: new Abstract: Interactive segmentation of 3D medical images supports quantitative analysis of anatomical structures and disease while allowing users to specify and re

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Sample, Simulate, Select: Physics-in-the-Loop Text-to-Motion for Humanoids Without Training

DGX agent

arXiv:2609.26420v1 Announce Type: new Abstract: Text-to-motion models generate plausible human motion but do not model a robot's dynamics; whole-body tracking controllers execute robot references reli

safetyarxiv-cs-ro

23 Sept 2026

Shallow to Deep: Aligning Token Pruning with Stage-wise Roles in LVLMs

arXiv:2609.25635v1 Announce Type: new Abstract: Large Vision-Language Models (LVLMs) incur high computational costs from redundant visual tokens. Although training-free attention-based multi-layer pru

Tutorials

Simulation-free Structure Learning for Stochastic Population Dynamics

arXiv:2510.16656v2 Announce Type: replace Abstract: Modeling dynamical systems and unraveling their underlying structural dependencies is central to many domains in the natural sciences. Various physi

tutorialsarxiv-cs-lg

Testing, not presuming, adequacy: calibrating generative social simulators against emergent network structure

model-releasesarxiv-cs-ai

arXiv:2609.24012v2 Announce Type: new Abstract: Validation of generative social simulators often stops at face validity: emergent network structure is compared descriptively, without quantified parame

TicTacBench: Benchmarking Timing Closure Capabilities of Coding Agents

model-releasesarxiv-cs-ai

arXiv:2609.23363v1 Announce Type: new Abstract: Recent advances in large language models (LLMs) have led to the emergence of coding agents capable of performing complex engineering tasks, including re

Topology-Aware Parameter-Efficient Adaptation for Cross-Dataset Retinal Vessel Segmentation

arXiv:2609.26189v1 Announce Type: new Abstract: Retinal vessel segmentation in multi-domain deployment requires a source model to adapt to domains that differ in imaging conditions and annotation conv

Transport-Coupled Bayesian Flows for Molecular Graph Generation

arXiv:2510.10211v4 Announce Type: replace Abstract: Molecular graph generation (MGG) is essentially a multi-class generative task, aimed at predicting categories of atoms and bonds under strict chemic

VeriSoftBench: Repository-Scale Formal Verification Benchmarks for Lean

arXiv:2602.18307v2 Announce Type: replace-cross Abstract: Large language models have achieved striking results in interactive theorem proving, particularly in Lean. However, most benchmarks for LLM-ba

A Lightweight Convolutional Neural Network for Real-Time Recognition of Hand-Drawn Geometric Shapes

arXiv:2609.24384v1 Announce Type: new Abstract: Recognizing hand-drawn geometric shapes is a foundational sub-problem of sketch recognition, with applications in education, human-computer interaction,

A vector logic for intensional formal semantics

arXiv:2602.02940v2 Announce Type: replace-cross Abstract: Formal semantics and distributional semantics are distinct approaches to linguistic meaning: the former models meaning as reference via model-

researcharxiv-cs-cl

AdaMerge: Tuning-Free Patch Compression for Multi-Vector Visual Document Retrieval

arXiv:2609.22562v1 Announce Type: new Abstract: Multi-vector visual document retrieval (VDR) models such as ColPali and ColNomic achieve strong accuracy by representing each document with hundreds to

An Unexpected Robot Policy: Early Evaluations of GPT-6 Astra on RoboDojo and Beyond

arXiv:2609.24170v1 Announce Type: new Abstract: Embodied AI systems are often organized into System 1 and System 2. System 1 is typically a pretrained policy that generates actions at high frequency,

AquaCap: A Training-Free Underwater Embodied Agent with Code-as-Policy

model-releasesarxiv-cs-ro

arXiv:2609.23133v1 Announce Type: new Abstract: Recent advances in vision-language-action models have stimulated growing interest in underwater embodied intelligence. However, their reliance on large-

Assessing Readability with LLMs: The Role of Reasoning and Few-Shot Prompting

arXiv:2609.24650v1 Announce Type: new Abstract: Readability assessment is essential for tailoring texts to intended audiences across educational, healthcare, and information retrieval domains. However

Balancing Reasoning and Hardware Constraints in RAG Pipelines for Ukrainian Multi-Domain Document Understanding

arXiv:2609.22124v1 Announce Type: new Abstract: This paper describes the system submitted to the UNLP 2026 Shared Task on Multi-Domain Document Understanding. The challenge required extracting precise

Bayesian Filtering in Physical Systems via Test-time Trained Flow Matching

arXiv:2609.23383v1 Announce Type: cross Abstract: Bayesian filtering provides a principled framework for online state estimation under uncertainty, yet its application to systems with high-dimensional

Belted Engression: Sufficient Dimension Reduction for Generative Distributional Regression

arXiv:2609.23789v1 Announce Type: new Abstract: Modern conditional generative models face significant challenges when learning complex covariate dependencies. While sufficient dimension reduction (SDR

Beyond Similarity: Coverage-Aware Prompt Selection for Time Series Forecasting with LLMs

arXiv:2609.22977v1 Announce Type: cross Abstract: Similarity-based retrieval is the dominant rule for conditioning large language models (LLMs) in in-context learning, retrieval-augmented generation,

Beyond the Text: Verifying That Agent-Written Papers Are Backed by Their Artifacts

arXiv:2609.22111v1 Announce Type: new Abstract: Large language model agents are increasingly capable of conducting research autonomously, producing research documents alongside the code and experiment

BizSage: A Self-Evolving Multi-Agent Framework for Business Research with Efficient Knowledge Retrieval

arXiv:2609.22235v1 Announce Type: new Abstract: While multi-agent systems based on large language models (LLMs) have shown promise in automating the progressive workflow of academic research, extendin

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BreakFun: Jailbreaking LLMs via Object Instantiation under Simulated Code Execution

arXiv:2510.17904v3 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are widely used because they process structures, syntax and code well, but this same ability also makes them para

safetyarxiv-cs-cl

Bridging Reconstruction and Generation: A Latent Distribution Perspective on Evaluation and Improvement

arXiv:2609.24088v1 Announce Type: new Abstract: In latent generative models, reconstruction quality is often assumed to correlate with generative performance. However, reconstruction FID (rFID) can ex

researcharxiv-cs-cv

Causilo Technical Report

arXiv:2609.22866v1 Announce Type: new Abstract: We introduce Causilo, a tabular foundation model (TFM) that combines frontier predictive performance with exceptionally fast inference. On TabArena, Cau

Applications

Contributions to the hierarchy of probabilistic languages

arXiv:2609.23567v1 Announce Type: cross Abstract: We reconsider the theory of probabilistic formal languages generated by n-gram models and by probabilistic context-free grammars (PCFGs). The expected

applicationsarxiv-cs-cl

Local Ai

Corrective Forcing: Unified Post-Training for Diffusions and Flows in Generative Speech Enhancement

arXiv:2609.24651v1 Announce Type: new Abstract: Diffusion and flow models, as promising generative paradigms for speech enhancement, face a training--inference mismatch: training uses analytical path

local-aiarxiv-cs-lg

Custom Named Entity Recognition and Topic Classification for Global Health Publications

arXiv:2609.24625v1 Announce Type: cross Abstract: How should natural language processing models be selected and adapted for global health literature in environments where annotated data and computatio

researcharxiv-cs-cl

Defusing Explosive Prompts: Understanding and Preventing Trigger-Based Prompt Injections in LLM Agents

arXiv:2609.22510v1 Announce Type: cross Abstract: As LLM applications integrate with external tools, they are increasingly exposed to indirect prompt injection (IPI), where adversarial instructions ar

Do LLMs Choose Like Humans? Using Cognitive Theory to Evaluate LLM Decision-Making

arXiv:2609.22225v1 Announce Type: new Abstract: Large language models (LLMs) exhibit a range of human-like decision-making behaviors, but whether these reflect similar underlying mechanisms or surface

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From Concept Alignment to Causal Grounding: An Intervention Test of Chain-of-Thought Faithfulness

arXiv:2609.23065v1 Announce Type: new Abstract: Chain-of-thought (CoT) can sound plausible yet be unfaithful to the model's underlying reasoning. Most prior work probes CoT faithfulness through input-

safetyarxiv-cs-cl

GameReplica: A Benchmark for Black-Box Visual Game Replication by Vision-Language Agents

arXiv:2609.22308v1 Announce Type: new Abstract: Coding-agent benchmarks usually evaluate implementation after the target behavior has been specified in text, code, or demonstrations. Existing research

Generalizable Optimal Control with Transformers: One Policy Across Diverse Systems

model-releasesarxiv-cs-ro

arXiv:2603.14910v2 Announce Type: replace-cross Abstract: Classical optimal control designs a separate controller for each plant. Even for the Linear Quadratic Regulator (LQR), every new model must be

Safety

GRACE: Grounded Adversarial Reasoning over Canadian Law

arXiv:2609.23726v1 Announce Type: new Abstract: Large language models have shown strong performance across a range of legal tasks, but existing benchmarks rarely evaluate the ability to take and defen

safetyarxiv-cs-cl

HyperCLIP++: Fine-tuning CLIP forOpen-vocabulary Semantic Segmentation in Hyperbolic Space

arXiv:2609.24564v1 Announce Type: new Abstract: CLIP, a foundational vision-language model, has emerged as a powerful tool for open-vocabulary semantic segmentation. While freezing CLIP's text encoder

Local Ai

Learning Prognostic Variables for AI Convective Parameterizations via Symbolic Distillation

arXiv:2609.24882v1 Announce Type: new Abstract: Hybrid AI-physics climate modeling aims to improve coarse (~100km-resolution) Earth system models by learning to parameterize subgrid processes from hig

local-aiarxiv-cs-lg

LegendBench: A Diagnostic Benchmark for Legend Understanding with Counterfactual Interventions

arXiv:2609.24172v1 Announce Type: new Abstract: Legends are fundamental to chart understanding, as reliable interpretation requires correctly binding legend entries to corresponding visual marks. Whil

LLaDA-PRM: A Bidirectional Step-Level Reasoning Evaluator

arXiv:2609.22700v1 Announce Type: new Abstract: Step-level reasoning evaluators are commonly based on autoregressive language models, whose causal attention restricts each step representation to the p

Low-Rank Frequency Convolution and Noise-Range Augmentation for Real-Time Pitch Estimation on Edge Devices

arXiv:2609.23340v1 Announce Type: cross Abstract: Pitch estimation on an edge device is constrained in three ways at once. The model must be small, it must stay accurate when the input is noisy, and o

researcharxiv-cs-lg

MemCalib: Benchmarking and Optimizing Memory Use in LLM Agents

arXiv:2609.24259v1 Announce Type: new Abstract: The effectiveness of agent memory ultimately depends on whether the underlying LLM gives each memory in context an appropriate degree of influence over

Merge++: Universal Merge Refinement Through Data-Free Checkpoint Inversion

arXiv:2609.22886v1 Announce Type: new Abstract: Model merging consolidates fine-tuned experts into one multi-task model without retraining. All existing data-free methods approach this problem entirel

researcharxiv-cs-lg

NAVIR: Neuromorphic Audio-Visual Speech Recognition for Robust Human-Robot Interaction on Edge Hardware

arXiv:2609.24391v1 Announce Type: new Abstract: Voice-controlled interaction in industrial settings is hampered by acoustic noise, which severely degrades audio-only speech recognition. Audio-visual s

On the Information-Theoretic Limits of Latent-Space Watermarking Through Pretrained Generators

arXiv:2609.24377v1 Announce Type: cross Abstract: We study latent-space watermarking through a pretrained generator using a prescribed latent-to-output stochastic mapping, called the renderer. A water

OSCAR: Order-aware Scoring and Calibration for AI Rankings

arXiv:2609.24128v1 Announce Type: cross Abstract: Judge-specific sensitivity is useful for aggregating pairwise LLM evaluations, but its interpretation depends on which systematic presentation effects

Perplexity Predicts Protection: Choosing Pretrained Backbones for Worst-Client Fairness in Federated Parameter-Efficient Fine-Tuning

arXiv:2609.23463v1 Announce Type: new Abstract: Federated learning lets multiple parties train a shared model without pooling their data, but a client with far less data than the others can end up poo

PrismGPT: Proxy-Guided Learning for Region-Aware Photo Editing with Self-Synthesized Reasoning

arXiv:2609.24768v1 Announce Type: new Abstract: Professional photo finishing relies on both global adjustments and region-specific local edits guided by semantic masks, yet current automated methods h

QLoRA Fine-Tuning of Ministral LLM for Sequence-to-Function Protein Annotation

arXiv:2609.24538v1 Announce Type: new Abstract: Functional annotation of newly sequenced proteins remains a bottleneck in molecular biology: the number of sequences in public repositories grows far fa

R-GEAN: Regimen-Guided Edit Action Network for Within-Admission Medication Change Prediction

arXiv:2609.22959v1 Announce Type: cross Abstract: The medications prescribed to a patient often change during a hospital admission as clinicians start, stop, or continue therapies. We study whether mo

Reassessing Global Gradient-Norm Imbalance in BLIP Fine-Tuning Across Physical Domains

arXiv:2609.23655v1 Announce Type: new Abstract: Imbalanced gradient magnitudes between the visual and language pathways of a vision-language model are often treated as a defect to be corrected. We tes