Search: “model-releases”

Weight Oracles: Reading Neural Network Weights with Language Models

arXiv:2610.07334v1 Announce Type: new Abstract: Interpretability methods for neural networks are predominantly reactive: they analyse activations produced during specific forward passes, requiring kno

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Model Releases

What the Elevation Map Cannot See: Semantic-Aware Locomotion and Execution-Aware Navigation for Humanoid Robot

DGX agent

arXiv:2610.07396v1 Announce Type: new Abstract: Navigation for humanoid robots is critical, yet large-scale evaluation on physical hardware is often impractical due to cost and safety concerns, making

model-releasesarxiv-cs-ro

7 Oct 2026

When Agent Context Goes Stale: Incoherence in Volatile Agent Context

arXiv:2610.05281v2 Announce Type: replace Abstract: Modern agents increasingly ground their reasoning in observations returned by tools, such as file contents read from a workspace. However, the data

When Explanations Compete: Policy-Aware Selection Under Uncertainty

arXiv:2410.05479v2 Announce Type: replace Abstract: Uncertainty-aware explanation methods often produce several alternatives for the same prediction. Selecting among them requires a policy for balanci

Where Do Two Populations of Persistence Diagrams Differ? Calibrated Local Inference at a Fixed Budget

arXiv:2610.08292v1 Announce Type: cross Abstract: Many two-sample tests for populations of persistence diagrams assess global differences without identifying the regions of the birth-death plane that

Who Wrote It Is Not Enough: Detecting Who Contributed the Insight

model-releasesarxiv-cs-cl

arXiv:2610.07365v1 Announce Type: new Abstract: As LLMs increasingly assist scientific writing and peer review, detecting who wrote the text is no longer sufficient: we need to determine who contribut

Will the Judge Flip? Predicting Position-Sensitive LLM Judgments from Residual Stream Activations

arXiv:2610.07115v1 Announce Type: cross Abstract: The order in which candidate responses are presented can change an LLM judge's verdict. Detecting such a position flip ordinarily requires judging eac

World Models' Last Exam in Physics

arXiv:2610.08791v1 Announce Type: new Abstract: Video world models can produce visually convincing yet physically inconsistent sequences, raising concerns about their reliability for prediction and pl

World Properties without World Models: Distributional Associations and the Interpretation of Decoding Results from Language Models

arXiv:2603.04317v2 Announce Type: replace-cross Abstract: A growing literature shows that variables can be linearly decoded from the activations of large language models (LLMs). These range from prope

WorldSolver: Can LLM Agents Simulate the Physical Dynamics via Solver Generation?

arXiv:2610.08720v1 Announce Type: new Abstract: LLM-based agents are increasingly advancing scientific and engineering problem solving, with physics simulation emerging as a challenging yet practical

Zero-Shot Visualization: Exploring Text Corpora with User-Prompted Axes

arXiv:2610.06889v1 Announce Type: cross Abstract: We study the application of large language models (LLMs) to the visual exploration of textual corpora. We introduce zero-shot visualization (ZSV), a t

zkLLMPoT: Efficient Zero Knowledge Proof of Training for Large Language Models

arXiv:2610.08258v1 Announce Type: new Abstract: Auditing the claimed outcomes of large language model (LLM) training is challenging when model weights and training data are private, while cryptographi

A Bird's-Eye View of Iterative Reward Design

arXiv:2610.04364v1 Announce Type: new Abstract: Designing effective reward functions in RL typically requires substantial expertise and trial and error. Recent work automates this process with LLM-bas

A differentiable Lagrangian-coupled 3D Gaussian Splatting-SPH model for forward simulation and inverse analysis in solid mechanics

arXiv:2610.04336v1 Announce Type: new Abstract: Recent advances in generative world models have increased interest in digital models that reproduce both the appearance of real objects and their respon

A Fine-Grained Analysis of the LoRA Fine-Tuning Landscape with Implications for Data Selection

arXiv:2610.06542v1 Announce Type: new Abstract: Low-Rank Adaptation (LoRA) has become a standard approach for parameter-efficient fine-tuning, yet a fundamental practical question remains unresolved:

A State Based Dispatch Controller for Hospital Delivery Robots with Shared Human and Infrastructure Resources

arXiv:2610.05971v1 Announce Type: new Abstract: Robot delivery studies can overstate transport capacity when travel to pickups and human support fall outside the modeled schedule. We formulate a locat

A Unified Scaling Law for Time Series Foundation Models

arXiv:2610.05269v1 Announce Type: new Abstract: We develop a Unified Scaling Law and a Unified Theory of Time Series Learning to understand how model capacity and historical information support foreca

Active-DiNTS: Active Differentiable Network Topology Search

arXiv:2610.04787v1 Announce Type: new Abstract: Neural Architecture Search (NAS) has proved to be a strong alternative to manual network design, but applying it to 3D medical image segmentation is lim

Adapting prior-data fitted networks for tabular anomaly detection

arXiv:2610.06693v1 Announce Type: new Abstract: While deep features have transformed anomaly detection in images and video, their impact on tabular data has been less substantial, partly due to the li

Adaptive Expert Guidance for Efficient On-Policy Reinforcement Learning

arXiv:2610.06019v1 Announce Type: new Abstract: With massively parallel simulation, on-policy Reinforcement Learning methods such as PPO have become standard in many domains. However, learning from sc

Adaptive Mean Flow for Responsive Closed-Loop Robot Control

arXiv:2610.06089v1 Announce Type: new Abstract: Diffusion- and flow-based robot policies have recently become widespread in robotic Imitation Learning (IL) due to their high performance and ability to

Adaptive-Shot Hybrid Quantum Anomaly Detection for Tactile Internet Security: Reliability-Aware Measurement Allocation Under Resource Constraints

arXiv:2610.05835v1 Announce Type: cross Abstract: Tactile Internet (TI) security analytics must balance reliable thresholded decisions with constrained computational and measurement resources. We stud

AdaSpark: Adaptive DSpark with Online Learning for Tree Verification and N-gram Fill

arXiv:2610.05774v1 Announce Type: new Abstract: Block drafters such as DSpark propose ranked candidates for several positions in one forward pass, and a tree verifier checks them in one pass of the ta

AgroGround: Multi-Granularity Grounded Recognition in Agriculture

arXiv:2610.04425v1 Announce Type: new Abstract: Agricultural visual models are typically evaluated for either recognition or localization, but reliable diagnosis requires identifying what is present a

AIProver: Agentic Auto-Formalization of Mathematical Research via Certificate-Driven Evolving Harness

arXiv:2610.05367v1 Announce Type: cross Abstract: Proof auto-formalization translates natural-language (NL) theorems and proofs into a formal language (FL) such as Lean, enabling mechanical verificati

All against the machine: the Solo score for rating skill in variable environments

arXiv:2610.04523v1 Announce Type: cross Abstract: We propose a distribution-free metric to rate individual skill in ``player-versus-environment'' settings, where participants face heterogeneous tasks

ALoDLM: Adaptively Looped Diffusion Language Models

arXiv:2610.04198v1 Announce Type: cross Abstract: Diffusion language models (DLMs) enable fast generation by predicting multiple tokens in parallel, but their practical adoption remains limited by a p

Analysis of SWIR Imaging Detection Performance Under Adverse Environmental Conditions for Autonomous Driving Systems

arXiv:2610.06596v1 Announce Type: new Abstract: Short-wave infrared (SWIR) imaging has emerged as a promising modality for autonomous driving, yet its practical benefits over RGB remain poorly charact

Anatomy of LLM Sycophancy: What a Flip Rate Hides

arXiv:2610.06522v1 Announce Type: cross Abstract: A model under pushback can correct itself, capitulate, or hold, and one flip rate counts a correction and a capitulation alike. Using SycoLens, a modu

AnchorPose for Geometry-Aware MOF Assembly through Meso-Grained Pose Generation

arXiv:2610.05843v1 Announce Type: cross Abstract: Predicting metal-organic framework (MOF) structures from given building blocks requires recovering their positions and orientations in a periodic crys

Answer with Evidence: Consistency-Aware Grounded Visual Question Answering for Roadside Traffic Scenes

arXiv:2610.05274v1 Announce Type: new Abstract: Roadside traffic reasoning requires every free-form textual claim to be backed by visual evidence. Existing grounded multimodal large language models (M

ANT: A Multi-Granularity Network Traffic Dataset and Benchmark for Agents Behavior Auditing

arXiv:2610.06514v1 Announce Type: cross Abstract: The growing adoption of large language model (LLM) agents creates a need for network administrators and security teams to audit agent behavior within

Anticipating the Consequences of Curriculum Decisions with Large Language Models

arXiv:2610.04604v1 Announce Type: new Abstract: Automatic curriculum learning can improve the effectiveness of reinforcement learning by selecting the training experiences presented to the agent over

Are We Measuring Anticipation? Auditing Privileged Information in Procedural Video Evaluation

arXiv:2610.03826v1 Announce Type: new Abstract: Benchmark scores license claims about the capabilities being evaluated. We audit the inference licensed by an evaluation protocol, rather than the predi

Arm-wise Compositional Generalization in Dual-Arm Vision-Language-Action Models

arXiv:2610.06184v1 Announce Type: new Abstract: Generalization in multi-arm collaboration can be studied as composing familiar atomic skills in new ways across arms. However, existing evaluations offe

ArtifactArena: Evaluating Models by What They Build in the Physical World

arXiv:2610.06511v1 Announce Type: new Abstract: To evaluate the frontier, we must measure models not by what they say, but by what they can engineer and build in grounded physical environments. We int

Assembling Insights for Agentic Machine Learning Engineering Systems

arXiv:2610.04927v1 Announce Type: cross Abstract: Agentic machine learning engineering (MLE) is an emerging AI4SE application for complex ML tasks and a step toward recursive self-improvement of AI sy

Asymptotically Optimal Best Arm Identification with Fixed-Budget under Differential Privacy

arXiv:2610.04600v1 Announce Type: new Abstract: Best arm identification under differential privacy is a pure-exploration problem in which both statistical efficiency and privacy protection must be ach

BabelFake: A Multilingual Audio-Visual DeepFake Benchmark

arXiv:2610.06339v1 Announce Type: new Abstract: Reliable and practical audio-visual DeepFake detection requires benchmarks that reflect diverse linguistic contexts and modern data synthesis pipelines

BARQ: Balanced Codebook Refinement for Low-Bit LLM Quantization

arXiv:2610.04490v1 Announce Type: new Abstract: As large language models (LLMs) grow in parameter count, model storage and parameter memory traffic have become major bottlenecks to efficient deploymen

Bayes-Sufficient Compression Is Not Enough: How Does Communication Help Multi-Agent Systems?

arXiv:2610.03769v1 Announce Type: new Abstract: Multi-agent LLM systems pair a sender with broad context and an executor with a limited local view. We study when a short message improves the executor'

Bayesian Optimization in Sequence-to-Architecture Latent Space for Zero-Shot NAS

arXiv:2610.06167v1 Announce Type: new Abstract: Zero-shot Neural Architecture Search removes the prohibitive cost of traditional NAS, but its search process is typically based on the evolutionary algo

BazaarBench: Delegation Safety in Decentralized C2C Marketplaces Run by LLM Agents

arXiv:2610.06748v1 Announce Type: cross Abstract: In decentralized consumer-to-consumer (C2C) marketplaces, people list goods, negotiate with strangers, and rate one another, so trust rests on reputat

Bellman-Centric Learning: Near-Optimal Regret for Linear Bandits with Memory

arXiv:2610.05659v1 Announce Type: new Abstract: We study linear bandits with memory, where past actions induce endogenous nonstationarity through an arbitrary known, bounded matrix-valued memory map.

Benchmarking Generative Trajectory Models for Active-Inference Control

arXiv:2610.05692v1 Announce Type: new Abstract: Learning from trajectory demonstrations offers a route to active-inference control of complex systems whose dynamics are difficult to model explicitly.

Beyond Masked Sparsity: SNACK Enables Truly Sparse Neural Networks on GPU

arXiv:2610.04093v1 Announce Type: new Abstract: Deep neural networks continue to grow in parameter count, driving up training and inference cost on GPUs. Sparse neural networks and Dynamic Sparse Trai

Beyond Overparameterization: Provable Learning of Input-Convex Multi-Layer Polynomial Networks with Active Queries

arXiv:2610.04999v1 Announce Type: new Abstract: The theoretical understanding of multi-layer neural networks is largely confined to overparameterized settings, which obscure parameter identifiability

Beyond Plausibility: Verifiable Fine-Grained Image Editing on Structured Assets

arXiv:2610.04381v1 Announce Type: new Abstract: Fine-grained image editing requires more than producing a visually plausible result: an editor must execute the requested attribute change precisely whi