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Hybrid Joint-Selective Optimization: Reduced-Space Levenberg-Marquardt Refinement of Low-Dimensional Parameters of Interest

model-releasesarxiv-cs-lg

arXiv:2609.37308v1 Announce Type: cross Abstract: This paper introduces a hybrid joint-selective optimization (HJSO) framework for large-scale numerical problems in which a small subset of trainable q

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Research

Hybrid Neural Simulation-Based Inference for Robust Applications and Limited-Budget Scenarios

DGX agent

arXiv:2609.36044v1 Announce Type: cross Abstract: We develop two hybrid techniques that approach the performance of neural simulation-based inference (NSBI) analyses while substantially reducing the c

researcharxiv-cs-lg

30 Sept 2026

HybridCUA: Learning to Orchestrate GUI and CLI for Computer-Use Agents

arXiv:2609.38008v1 Announce Type: new Abstract: Computer use agents (CUAs) have demonstrated strong capabilities in completing digital tasks. However, existing CUAs either rely solely on graphical use

tutorialsarxiv-cs-cv

HyDI: A hybrid Deep Learning-Inductive Logic Programming ensemble for multi-label classification

arXiv:2609.37740v1 Announce Type: new Abstract: While attaining remarkable results for many applications, Deep Learning models are notoriously difficult to explain. This work introduces HyDI, a hybrid

Hyper Yoshimura: How a slight tweak on a classical folding pattern unleashes meta-stability for deployable robots

arXiv:2505.09919v3 Announce Type: replace Abstract: Deployable structures inspired by origami have provided lightweight, compact, and reconfigurable solutions for various robotic and architectural app

researcharxiv-cs-ro

HyperSAM: A Promptable Foundation Model for Hyperspectral Remote Sensing

arXiv:2609.37340v1 Announce Type: new Abstract: Hyperspectral remote sensing provides dense spectral measurements that are indispensable for material-level Earth observation, yet the construction of a

researcharxiv-cs-cv

Hyperspherical Semantic Trajectory Analysis: Mapping Technological Diffusion across Academic Preprints, Patent Signals, and Compute Scaling

arXiv:2609.35845v1 Announce Type: new Abstract: Macroeconomic productivity metrics, such as Total Factor Productivity, register technological breakthroughs with multi-year reporting lags due to admini

researcharxiv-cs-cl

HyperZip: Efficient Data Compression through Personalized Diffusion LLMs with Hypernetworks

arXiv:2609.36357v1 Announce Type: new Abstract: Large language models (LLMs) have shown strong potential for lossless data compression, but existing approaches are constrained by the high computationa

Identifiability Guarantees for Drivers and Dynamics of Delayed Physical Systems

model-releasesarxiv-cs-lg

arXiv:2609.37944v2 Announce Type: cross Abstract: A wide range of methods have been proposed, including physics-informed neural networks, which are powerful but do not guarantee identifiability of the

Identifying ODEs from Unstructured Data with Causal Representation Learning

arXiv:2609.37083v1 Announce Type: cross Abstract: We study the problem of recovering the governing ODE of a dynamical system from unstructured, high-dimensional observations such as images. Existing m

IESR:Efficient MCTS-Based Modular Reasoning for Text-to-SQL with Large Language Models

model-releasesarxiv-cs-cl

arXiv:2602.05385v2 Announce Type: replace Abstract: Text-to-SQL is a key natural language processing task that maps natural language questions to SQL queries, enabling intuitive interaction with web-b

Illusory Truth or Mere Exposure? Model-Dependent Repetition Effects in LLM-Based Social Media Simulations

arXiv:2609.36278v1 Announce Type: new Abstract: Generative agent-based models (GABMs) are increasingly used to simulate social media dynamics, including misinformation spread. For such social simulati

Imagine3D-LLM: Teaching MLLMs to Imagine 3D Scenes Before Answering

arXiv:2609.38177v1 Announce Type: cross Abstract: Reasoning about the 3D world from multi-view images remains a fundamental challenge for Multimodal Large Language Models (MLLMs). While modern MLLMs h

researcharxiv-cs-cl

ImbalancE: Inference-Time Latent Search Against Degree Imbalance in Link Prediction

arXiv:2609.36996v1 Announce Type: new Abstract: Knowledge Graph Embedding models have been extensively used to learn representations of entities and relations in Knowledge Graphs for predicting missin

Implementing Cumulative Functions with Generalized Cumulative Constraints

arXiv:2508.01751v3 Announce Type: replace Abstract: Modeling scheduling problems with conditional time intervals and cumulative functions has become a common approach when using modern commercial cons

Improved Distributional Diffusion Models

arXiv:2609.37147v1 Announce Type: new Abstract: Distributional Diffusion Models (DDMs) replace the standard mean-prediction denoiser with a distributional denoiser trained via a scoring rule objective

researcharxiv-cs-cv

Improving Function Space Flow Matching with Kernel Optimal Transport

model-releasesarxiv-cs-lg

arXiv:2609.38049v1 Announce Type: new Abstract: Generative models for function-valued data, such as time series and solutions of partial differential equations, must learn distributions over infinite-

Improving scalable oversight with co-trained monitors

arXiv:2609.36049v1 Announce Type: cross Abstract: Worker-monitor setups are a promising approach to AI oversight, but training workers against fixed monitors can incentivize monitor evasion. We study

safetyarxiv-cs-ai

In-Context Learning Amplifies a Latent Symbolic Circuit

arXiv:2609.36265v1 Announce Type: cross Abstract: Large language models can learn abstract rules from just a few in-context examples, but how their internal mechanisms activate as examples accumulate

tutorialsarxiv-cs-ai

Agents

In-Context Learning for Robots: Methods and Applications

arXiv:2609.36012v1 Announce Type: new Abstract: General-purpose robots must infer what a new task requires and translate that understanding into appropriate physical action. In-context learning (ICL)

agentsarxiv-cs-ro

Applications

In-context Robot Learning Made Simple: A Democratized Recipe for Manipulation Tasks

arXiv:2609.38173v1 Announce Type: new Abstract: We study robotic in-context learning (ICL), an emerging paradigm that enables robots to infer and execute tasks from visual demonstrations. Despite its

applicationsarxiv-cs-ro

Applications

Independent Verification Paths Are Not Independent: A Case Study of Common-Mode Failure in a Satellite Catalogue Pipeline

arXiv:2609.37603v1 Announce Type: cross Abstract: A common safeguard for a data pipeline is redundant computation: derive each published number by two routes built on different technology and refuse t

applicationsarxiv-cs-ai

Inducing Process Supervision from Outcome-Only Reinforcement Learning

arXiv:2609.36641v1 Announce Type: cross Abstract: Process reward models (PRMs) have become a key component for LLMs, as their step-level feedback supports both post-training and test-time reasoning. H

Inferring Soil Friction Angle from Robot Foot-Ground Force Histories: A Bayesian Inverse Approach to Proprioceptive Soil Sensing

arXiv:2609.36582v1 Announce Type: new Abstract: Foot-ground interaction signals recorded by quadruped robots may enable spatially distributed, in situ characterization of soil strength. As a first ste

researcharxiv-cs-ro

Information Bottleneck-Guided Adaptive Hypergraph Transformer for Brain Disease Diagnosis

arXiv:2609.37220v1 Announce Type: new Abstract: Exploring high-order correlations and long-range dependencies in brain networks holds significant value for both neuroscience research and clinical diag

tutorialsarxiv-cs-ai

Information-theoretic receding-horizon active learning of nonlinear dynamical systems

arXiv:2609.36712v1 Announce Type: cross Abstract: Accurately learning nonlinear dynamics from a finite-duration experiment requires the efficient collection of informative data. We address this challe

Infrared Subtraction with Artificial Intelligence

arXiv:2609.36007v1 Announce Type: cross Abstract: We present AI-developed local infrared subtraction, building on projection to Born and EFT matching. The framework separates an integrable radiation t

InsightMap: Structured Spatial Modeling for Embodied Multimodal Reasoning

arXiv:2609.37187v1 Announce Type: new Abstract: Language-guided navigation requires connecting partial observations to a persistent spatial reference and learning how actions change that representatio

researcharxiv-cs-cv

Inter-patient ECG Arrhythmia Classification with LGNs and LUTNs

arXiv:2601.11433v2 Announce Type: replace Abstract: Deep Differentiable Logic Gate Networks (LGNs) and Lookup Table Networks (LUTNs) are demonstrated to be suitable for the automatic classification of

Interacting particle guidance for sampling reward-tilted generative priors

arXiv:2609.37227v1 Announce Type: new Abstract: Inference-time steering adapts pretrained diffusion and flow-based models to new tasks, e.g., to generate samples from a conditional distribution or sam

safetyarxiv-cs-lg

Interactive-Policy Distillation with Bidirectional Propose-and-Verify

arXiv:2609.36546v1 Announce Type: cross Abstract: On-policy distillation (OPD) trains a student model on its self-generated trajectories with dense token-level teacher feedback. However, naive OPD may

InterBias-SV: Compound Conditions in Speaker Verification

arXiv:2609.36500v1 Announce Type: cross Abstract: Speaker verification systems encounter combinations of noise, channel distortion, and changes in speech. Evaluating each condition separately does not

Interpolated Policy Distillation: A Controllable Continuum Between Off-Policy and On-Policy Distillation

arXiv:2609.37170v1 Announce Type: cross Abstract: Off-policy and on-policy distillation have traditionally been formulated as separate paradigms, each favoring a different property of distillation tra

safetyarxiv-cs-ai

Interpretable intrinsic dimension estimation through componentwise calibration of distance and angle

arXiv:2609.37114v1 Announce Type: new Abstract: DANCo (Dimensionality from Angle and Norm Concentration) jointly calibrates nearest-neighbor distance and angular statistics and consistently reaches st

Into the danger zone: stable extrapolation in high-dimensional function and operator learning

arXiv:2609.36709v1 Announce Type: cross Abstract: Out-of-distribution (OOD) generalization is a central challenge in scientific machine learning. We study regression problems in which the test distrib

Intrinsic Associative Memory on Riemannian Manifolds: Curvature, Capacity, and Emergent Modes

arXiv:2609.35948v1 Announce Type: cross Abstract: Geometry does more than constrain an associative memory: curvature determines what it remembers and which states it creates. We develop intrinsic dens

Introducing the CZAR Loss: A Tailored Objective Function for Financial Log-Return Predictions

arXiv:2609.36061v1 Announce Type: new Abstract: In quantitative finance, standard regression losses are misaligned with the economics of return prediction. As the conditional mean of financial log-ret

safetyarxiv-cs-lg

Local Ai

Invariant Atoms: Sparse Coordinates of Local Semantic Geometry in Language Model Representations

arXiv:2609.36451v1 Announce Type: cross Abstract: Large language models often preserve meaning despite substantial changes in wording, style, and syntax, while small semantic edits can systematically

local-aiarxiv-cs-cl

IronLLM: Forging Compact Edge-Native Language Models for Real-Time Embodied Intelligence

arXiv:2609.36860v1 Announce Type: new Abstract: We present IronLLM-0.6B, a 654M-parameter language model designed for efficient on-device inference. IronLLM-0.6B combines a hybrid attention architectu

Agents

Is Agent Code Less Maintainable Than Human Code?

arXiv:2606.21804v2 Announce Type: replace-cross Abstract: Maintainability is a core dimension of software engineering, shaping how code is written, reviewed, and developed over time. While coding agen

agentsarxiv-cs-ai

Is Human-Readable Text Necessary for Effective LLM Fine-Tuning?

arXiv:2609.35868v1 Announce Type: new Abstract: Is human readability necessary for effective fine-tuning of large language models? We investigate whether model-conditioned training representations can

Agents

Is manual software optimization a thing of the past?

arXiv:2609.37849v1 Announce Type: cross Abstract: Scientific software is increasingly required to process larger datasets while maintaining acceptable execution times. Software optimization traditiona

agentsarxiv-cs-ai

Iterative Exact Discrete Guidance for Energy-Based Sampling

arXiv:2609.37043v1 Announce Type: new Abstract: Sampling from unnormalized distributions over large discrete state spaces becomes difficult when a multimodal target is far from a tractable reference.

tutorialsarxiv-cs-lg

It's All Training: A Fully Synthetic Single-Stage Recipe for LLMs

arXiv:2609.37891v1 Announce Type: new Abstract: Current pre-training datasets are derived from web crawls, with all their issues, and were not designed to support mid- and post-training pipelines--for

researcharxiv-cs-cl

It's Not What the Image Shows: Irrelevant Context Destabilises VLM Judges Without Informing Them

arXiv:2609.37863v1 Announce Type: cross Abstract: Vision-language models (VLMs) are increasingly used in place of human annotators, making it important that substitutability tests reflect the model ra

Jaxolotl: A Unified High-Performance Benchmark Suite for LTL-Based Multi-Task RL

arXiv:2609.38065v1 Announce Type: cross Abstract: Training agents to follow arbitrary instructions is an important goal of multi-task reinforcement learning (RL). Linear temporal logic (LTL) provides

JEV-as-a-Judge: Accept When Confident, Escalate When Unsure

arXiv:2609.26550v3 Announce Type: replace Abstract: LLM-as-a-judge scales evaluation, but reasoning judges are slow and costly. We study JEV-as-a-Judge: evaluation with JEV, a decision-only judge that

JointEdit3D: Feed-Forward 3D Scene Editing in a Unified Latent Space

model-releasesarxiv-cs-cv

arXiv:2606.13345v2 Announce Type: replace Abstract: Existing 3D scene editing methods typically rely on per-scene optimization over explicit 3D representations or cascaded edit-and-reconstruct pipelin