All entries

Objects Without Morphisms: What LLMs for Mathematics Do Not Represent

arXiv:2610.03551v1 Announce Type: new Abstract: Large language models (LLMs) have reached expert-level performance on competition mathematics largely through the volume of search placed around them: c

Source

Human DGX agent

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Octrees as an Explicit 3D Language

DGX agent

arXiv:2610.02388v1 Announce Type: new Abstract: Existing 3D large language models (LLMs) compromise on two fronts: they compress shapes into latent codebook indices or coordinate text, which removes s

researcharxiv-cs-cv

5 Oct 2026

OLMo-Detect: A Multi-Stage, Confounder-Controlled Benchmark for Membership Inference on Large Language Models

arXiv:2610.02986v1 Announce Type: new Abstract: Membership inference on large language models (LLMs) aims to determine whether a given text sample was included in an LLM's training data, without acces

OmniAct3D: Leveraging Foundation Geometry and Evidence-Grounded Reasoning for Panoramic 3D Detection

arXiv:2610.03015v1 Announce Type: cross Abstract: Accurate 3D detection is essential for mobile embodied agents, while Vision Foundation Models (VFMs) offer transferable visual and geometric priors. Y

OmniConfess: Eliciting Token Confessions to Mitigate Omni-Modal Hallucination

arXiv:2610.02999v1 Announce Type: new Abstract: Omni-modal large language models (OmniLLMs) unify text, images, audio, and video, yet hallucinate when generation relies on the wrong evidence. Existing

Local Ai

On-Board Anomaly Detection for Efficient Marine Environmental Monitoring

arXiv:2610.03649v1 Announce Type: cross Abstract: Marine ecosystems are impacted by various threats such as oil spills, algal blooms, and sediment floods, which disrupt habitats, wildlife, and human a

local-aiarxiv-cs-ai

Local Ai

On-Premises Multi-Course RAG Tutoring for Business Education: Hardware-Software Trade-offs in a Campus AI Tutor

arXiv:2610.02510v1 Announce Type: new Abstract: Campus AI tutors based on retrieval-augmented generation (RAG) must ground answers in assigned course materials while keeping textbooks and student dial

local-aiarxiv-cs-ai

On Representational Alignment among Embodied Agents

arXiv:2610.02985v1 Announce Type: new Abstract: Embodied agents interacting with the same physical process may maintain heterogeneous, asynchronous, and observer-relative representations. Rather than

safetyarxiv-cs-ro

On the Chain-of-Thought Monitorability of Looped Language Models

arXiv:2610.02741v1 Announce Type: new Abstract: Chain-of-thought (CoT) monitoring provides a promising approach for detecting undesirable model behavior. Looped language models (LoopLMs) repeatedly ap

On the Convergence of Success Conditioning for Policy Optimization

arXiv:2610.03642v1 Announce Type: new Abstract: Success conditioning is a strategy for improving decision-making policies in stochastic environments; it updates a policy by increasing the probability

On the Tip of the Tongue: Why LLMs Hallucinate Answers They Can Decode

arXiv:2603.13911v2 Announce Type: replace Abstract: A language model can give the wrong answer even when the correct answer is decodable from its intermediate states. To study this gap between decodab

On Unlearning for Time-series Forecasting

arXiv:2610.02865v1 Announce Type: new Abstract: Time-series forecasting is widely used in sensitive domains. Models in these settings are often trained on longitudinal user- or entity-level records, w

One Photon, Many Worlds: Posteriors and Predictions with Single-Photon Cameras

arXiv:2610.02675v1 Announce Type: cross Abstract: Single-photon avalanche diode (SPAD) cameras operate fundamentally differently from conventional cameras due to their photon-counting nature. Each fra

researcharxiv-cs-cv

Online Verification of Language Model Responses Under Cost Constraints

arXiv:2610.02632v1 Announce Type: new Abstract: As large language models are increasingly deployed for multi-step reasoning, verifying the correctness of their outputs has become essential for maintai

Ontological Instability and Statistical Amplification: The Paradox of 'Humanizing' LLM-Generated Text

arXiv:2610.03110v1 Announce Type: new Abstract: Supervised AI-text detectors report high benchmark accuracy, but it is not clear what their decisions are based on. We analyze a RoBERTa-based detector

OPD Before RL: Warm-Starting Rubric-Based RL with On-Policy Distillation

arXiv:2610.02781v1 Announce Type: cross Abstract: Many useful language-model tasks cannot be evaluated by exact outcome verification. Rubric-based reinforcement learning (RL) addresses this issue by s

safetyarxiv-cs-ai

Open-Endedness Bench: Measuring Epistemic Process from Agent Records

arXiv:2610.02588v1 Announce Type: new Abstract: Agents are increasingly given open-ended research tasks: discovering an empirical law from self-designed experiments, improving a heuristic whose optimu

OpenBox: Annotate Any Bounding Boxes in 3D

arXiv:2512.01352v2 Announce Type: replace Abstract: Unsupervised and open-vocabulary 3D object detection have recently gained attention, particularly in autonomous driving, where reducing annotation c

safetyarxiv-cs-cv

OpenGameEval: Benchmarking Agentic Programming and Exploration in a Stateful Game Engine

arXiv:2610.02563v1 Announce Type: cross Abstract: We present OpenGameEval, a benchmark and evaluation framework for agentic game development inside Roblox Studio. It runs language models as agents in

OpenRUA: Robot-Use Agents Are Zero-Shot Visuomotor Policies

model-releasesarxiv-cs-ro

arXiv:2610.02459v1 Announce Type: new Abstract: Coding agents are extending their reach into the physical world by writing and executing robot control programs. One might expect the agents to use the

Operator Calculus for Population-Based Optimization: Modular Convergence and Finite-Population Guarantees

arXiv:2606.14289v2 Announce Type: replace-cross Abstract: Population-based optimizers combine update rules such as mutation, selection, and recombination. When one rule changes, it is often unclear wh

Operator-informed initialization for Fourier features physics-informed neural networks

arXiv:2610.03378v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) typically exhibit spectral bias, where some frequencies of the target function converge more slowly than others

Agents

Optimal Planning in a Dynamic World

arXiv:2610.03312v1 Announce Type: new Abstract: Background: We address the problem of planning when the set of feasible states or actions changes over time. For example, in the problem of path plannin

agentsarxiv-cs-ai

OptiSelect: How does the Optimizer Shape Data Curriculum?

arXiv:2610.03432v1 Announce Type: cross Abstract: Online data selection has demonstrated substantial efficiency gains for LLM pretraining by training on the most valuable candidates within each batch.

Oracle headroom without signal: null-calibrated evaluation of candidate selection for thermal heart rate estimation

arXiv:2610.02561v1 Announce Type: new Abstract: Camera-based physiological monitoring can produce multiple estimates from several facial regions, extraction methods, and processing settings. Signal qu

researcharxiv-cs-cv

OuroReward: Sequential Reward Scheduling for Reinforcement Learning in Text-to-3D Generation

arXiv:2610.03423v1 Announce Type: new Abstract: Reinforcement learning (RL) for Text-to-3D (T23D) generation requires optimization across multiple quality dimensions such as semantic alignment and tex

safetyarxiv-cs-cv

Out of Sync, Out of Sight: Phantom State Attacks against IIoT Intrusion Detection

arXiv:2610.02552v1 Announce Type: cross Abstract: Machine learning-based intrusion detection systems (IDS) are critical for securing Industrial Internet of Things (IIoT) environments. Most adversarial

Output Language Confusion under Multilingual Prompt Contamination

arXiv:2610.02926v1 Announce Type: new Abstract: Standard factual benchmarks assume clean monolingual prompts and exact-match scoring, two assumptions that break simultaneously in real-world multilingu

Overcoming Challenges of Interpretive Structural Modeling with Large Language Models

arXiv:2610.02254v1 Announce Type: cross Abstract: Interpretive Structural Modeling (ISM) is a well-known process for multi-criteria decision making. The success of ISM over other methodologies is its

Page-EntroKV: Hardware-Aligned, Entropy-Weighted KV-Cache Eviction under Grouped-Query Attention

arXiv:2610.03135v1 Announce Type: new Abstract: Serving long-context autoregressive language models is constrained by the key-value (KV) cache. Most dynamic eviction methods score token importance per

PaMIR: Open Benchmark of Public Credit-Default Datasets

arXiv:2610.03259v1 Announce Type: new Abstract: We release PaMIR (Public Arrival-ordered Measurement for Inference in Risk), an open benchmark for credit-default prediction when labels are scarce and

Tutorials

PAPER2LLM++: Continual Self-Evolution of LLMs from Research Papers

arXiv:2610.02793v1 Announce Type: new Abstract: Research on LLMs continually uncovers model limitations, their causes, and potential solutions. Yet these human discoveries remain largely disconnected

tutorialsarxiv-cs-ai

ParaGeo: Decomposing Paralinguistic Variation into a Shared Latent Geometry

arXiv:2610.03125v1 Announce Type: cross Abstract: Speech delivery varies with both the requested paralinguistic attribute and the linguistic content. We introduce ParaGeo, a matched-content decomposit

Parameter-Free Interval-Dynamic Regret under Heavy-Tailed Noise

arXiv:2610.02258v1 Announce Type: new Abstract: We study online convex optimization with one unbiased stochastic subgradient per round and an unknown finite conditional pth noise moment, 1<ple2. For e

Parasitic Co-Denoising: Unlocking 3D Human Motion Generation in a Frozen Video Diffusion Model

arXiv:2610.03047v1 Announce Type: new Abstract: Despite never being supervised on explicit 3D motion, large-scale text-to-video diffusion models synthesize realistic human motion in their generated vi

safetyarxiv-cs-cv

Passing the Test You Trained On: Re-evaluating Prompt-Injection Detectors for LLM Agents

arXiv:2610.03448v1 Announce Type: cross Abstract: LLM agents increasingly screen tool outputs with small prompt-injection detectors, and teams choose among detectors by their scores on public benchmar

Peer Effects in Signed Networks: Separating Influence Through Positive and Negative Ties

arXiv:2610.02872v1 Announce Type: new Abstract: Evaluating network interventions requires understanding how treatment affects people through their social relationships. Counting treated neighbors with

Agents

Peer Influence across Heterogeneous AI Models

arXiv:2610.03095v1 Announce Type: new Abstract: When two AI agents disagree, who persuades whom? As multi-agent systems increasingly combine language models of different families and sizes, the answer

agentsarxiv-cs-ai

Performance Evaluation of Ising and QUBO Variable Encodings in Boltzmann Machine Learning

arXiv:2510.13210v2 Announce Type: replace Abstract: We compare Ising ({-1, +1}) and QUBO ({0, 1}) encodings for Boltzmann machine learning under controlled protocols that fix the sampler, optimizer, a

Agents

Permutation Robustness Is Not Enough: Action Collapse in Multi-Agent Transformer Policies

arXiv:2610.02848v1 Announce Type: cross Abstract: Transformer policies are attractive for multi-agent robot learning because self-attention can model interactions among agents. However, multi-agent te

agentsarxiv-cs-lg

Personalized Automatic Speech Recognition for a Dysarthric and Tracheostomic Speaker using Artificial Conversations

arXiv:2610.03017v1 Announce Type: new Abstract: This work presents an automatic speech recognition (ASR) system personalized for a Czech speaker with a permanent tracheal stoma and severe dysarthria r

Physical AI Smart Spaces: A Large-Scale Benchmark for Multi-Camera 3D Perception in Smart Spaces

model-releasesarxiv-cs-cv

arXiv:2610.02580v1 Announce Type: new Abstract: Physical AI Smart Spaces is, to the best of our knowledge, the first benchmark to simultaneously provide large-scale, multi-class, and multi-camera 3D p

Pincer: Resource Authorization for Agents using a Digital Twin

arXiv:2610.02569v1 Announce Type: cross Abstract: Coding agents have become increasingly long-horizon, autonomous, reliant on general-purpose shell and maintain their own persistent memory for self-im

Pivot-SD: Efficient Self-Distillation for Masked Diffusion Language Models

arXiv:2610.03665v1 Announce Type: cross Abstract: Masked diffusion language models (dLMs) offer a promising parallel alternative to autoregressive models for complex reasoning. However, they face a di

researcharxiv-cs-cl

Planning to Learn

arXiv:2610.03667v1 Announce Type: new Abstract: Policy-gradient methods are central to modern reinforcement learning, including LLM post-training. When they struggle, the usual suspects are exploratio

PLCWorld: Benchmarking LLM-Generated PLC Programs in Closed-Loop Plant Simulation

arXiv:2610.02982v1 Announce Type: new Abstract: Programmable logic controllers (PLCs) coordinate industrial equipment by reading sensor inputs and issuing control commands. Evaluating whether large la

PocketSplat: Mobile Gaussian Reconstruction via World-Space Latent Allocatio

arXiv:2610.03192v1 Announce Type: new Abstract: Mobile Gaussian reconstruction must satisfy two requirements: the reconstruction model must execute within a device resource envelope, and the resulting

researcharxiv-cs-cv

PoCoFL: POlicy-COmpliant Federated Learning

arXiv:2610.03650v1 Announce Type: cross Abstract: Federated Learning (FL) is a privacy-oriented learning paradigm that enables collaborative model training while keeping training data local to partici