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The Effect of Gait Stability Based on Two Types of Impact Strategies for Two-Link Walking and Brachiating Robots

arXiv:2610.01004v1 Announce Type: cross Abstract: In this paper, we explore the impulsive dynamics common to single-joint, two-link models of walking and brachiating gaits with respect to slope and sw

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The Geometry of Time: Horizon-Independent Feasibility and Repair for STL

DGX agent

arXiv:2610.00199v1 Announce Type: cross Abstract: Signal Temporal Logic control synthesis frequently encounters physical infeasibility due to actuator limits or flawed task deadlines. Standard optimiz

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2 Oct 2026

The Life Cycle of a Massive Activation: Stochastic Birth, Weight-Decay-Driven Growth, and Competitive Consolidation

arXiv:2610.00423v1 Announce Type: cross Abstract: Massive activations, residual-stream coordinates with magnitudes far larger than typical activations, are associated with attention sinks in transform

The Price of Correlated Tests: How Strict Should a Model Release Gate Be?

arXiv:2610.00993v1 Announce Type: cross Abstract: Before a machine learning model ships, it often has to pass a suite of automated tests. Requiring every test to pass looks safe, yet it can reject man

Tight Transition Time Bounds for Separable Logistic Regression at the Edge of Stability

arXiv:2610.01459v1 Announce Type: new Abstract: We study logistic regression on linearly separable data under gradient descent with a large constant stepsize eta. Such dynamics may exhibit a character

Toward Humanoid Robots in Construction: A Teleoperation Feasibility Study

arXiv:2610.00718v1 Announce Type: new Abstract: We present a teleoperation system that enables a single operator to perform construction tasks on a Unitree G1 humanoid, combining extended reality (XR)

Towards Physical Underwater Robotic Assistance for Scuba Diver Movement in Confined Spaces

arXiv:2610.01906v1 Announce Type: new Abstract: Scuba divers are taught to control their depth to avoid rapid ascents and descents, which could result in serious injuries such as gas embolisms and bar

TRACE: Privacy-Preserving Next-Best-View Selection over Distributed 3D Gaussian-Splat Maps

arXiv:2610.00822v1 Announce Type: new Abstract: Share the light, not the map. We study next-best-view selection for a team of robots, each of which builds its own 3D Gaussian Splatting map and keeps i

Training-Aware Target Coverage for Synthetic Data Selection

arXiv:2610.00814v1 Announce Type: cross Abstract: Synthetic data are increasingly used to scale LLM training, yet more synthetic data do not necessarily produce better models. Useful synthetic data mu

Trajectory Stitching for Solving Inverse Problems with Flow-Based Models

arXiv:2602.08538v2 Announce Type: replace-cross Abstract: Flow-based generative models have emerged as powerful priors for solving inverse problems. One option is to directly optimize the initial late

Transferable Graph Metanetworks

arXiv:2610.00420v1 Announce Type: cross Abstract: A weight space network (or metanetwork) takes the weights of another neural network as input and predicts properties of it. Most prior work trains suc

Uncertainty-Aware Learning from Multi-Expert Interval Targets

arXiv:2610.00102v1 Announce Type: new Abstract: Many machine learning (ML) applications rely on expert labels, and qualified experts may provide different but plausible interpretations of the same obs

Understanding Latent Diffusability via Fisher Geometry

arXiv:2604.02751v3 Announce Type: replace Abstract: Diffusion models often degrade in latent spaces, yet the formal causes remain poorly understood. We quantify latent-space diffusability via the rate

UniGuardian: A Unified Defense for Detecting Prompt Injection, Backdoor Attacks and Adversarial Attacks in Large Language Models

arXiv:2502.13141v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) are vulnerable to attacks like prompt injection, backdoor attacks, and adversarial attacks, which manipulate prom

Universal Byte-Level Encoding: UTF-8/UTF-16 Routing to Reduce Cross-Script Token-Budget Disparities

arXiv:2610.01984v1 Announce Type: cross Abstract: Byte-level byte-pair encoding (BBPE) tokenizers are attractive for multilingual large language models (LLMs) because they cover all Unicode text. In U

VANDAM: Viewing a nucleotide sequence with DNA molecular priors

arXiv:2610.00411v1 Announce Type: new Abstract: Contemporary Genomic Foundation Models (GFMs) rely on a DNA-as-a-string paradigm that employs masked token prediction objectives for pretraining. Howeve

Variational Streaming Flow: Probabilistic Forecasting in Physical Time

arXiv:2610.00976v1 Announce Type: new Abstract: Probabilistic forecasting is important for predicting complex dynamical systems because intrinsic randomness and incomplete observations can cause the s

VASC: Value-Aware Sparse Attention with Cross-Layer Memory for Efficient 3D Reconstruction

arXiv:2610.01013v1 Announce Type: new Abstract: Feed-forward 3D vision models such as VGGT have achieved remarkable progress, unifying camera estimation and dense scene reconstruction in a single pass

Verbalized and Internal Probabilities Are Coupled in Large Language Models

arXiv:2610.00827v1 Announce Type: cross Abstract: Large language models carry an internal notion of uncertainty in their sampling distribution, i.e., the probabilities they place on generating one ans

VETO: Video Efficient Token Optimization for Vision Language Models

arXiv:2610.01785v1 Announce Type: cross Abstract: Processing long videos with Vision-Language Models (VLMs) is bottlenecked by the quadratic cost of visual tokens, making long-form inference prohibiti

VideoSTF: Stress-Testing Output Repetition in Video Large Language Models

arXiv:2602.10639v2 Announce Type: replace Abstract: Video Large Language Models (VideoLLMs) have achieved strong performance on video understanding tasks, yet existing benchmarks evaluate only what mo

VITA: A Multi-Source Vicinal Transfer Augmentation Method for Out-of-Distribution Generalization

arXiv:2204.11531v2 Announce Type: replace Abstract: Invariance to diverse types of image corruption, such as noise, blurring, or colour shifts, is essential to establish robust models in computer visi

VTV-FM: Flow Matching through Variational Terminal-Velocity Closure

arXiv:2610.00785v1 Announce Type: new Abstract: Flow matching (FM) learns generative transport by fitting continuous-time motion from a simple source distribution to the data distribution. Most existi

WaLLM -- Understanding Use and Engagement with a General-Purpose LLM on WhatsApp

arXiv:2505.08894v2 Announce Type: replace-cross Abstract: Large language model (LLM) chatbots are increasingly reaching users through messaging platforms (e.g. WhatsApp). However, these systems remain

Wasserstein Gradient Flows and Forward-Only Diffusion Are Not Enough for Multimodal Sampling

arXiv:2610.02081v1 Announce Type: cross Abstract: There has been a proliferation of sampling algorithms based on Wasserstein gradient flows (WGF) and forward-only diffusion processes (FODP), often acc

Watch Your Speech: Text-aware Video-to-Speech Synthesis with Textual Conditioning

arXiv:2610.01012v1 Announce Type: new Abstract: Video-to-speech synthesis aims to generate natural-sounding speech from silent talking-face videos while ensuring phonetic accuracy. A fundamental chall

Weighted Data Selection: Sharp Upper-Half and Five-Dimensional Laws

arXiv:2610.00101v1 Announce Type: cross Abstract: How much risk does a small reweighted training support retain? For finite weighted least squares with the minimum-norm learner, we prove the exact law

We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks: Writing. Something I'v…

We'll be spending a lot more time trying to understand the outputs of language models. A few thoughts, tips & tricks: Writing. Something I've had success with: Ask your LLM to explain something in ASD

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What Can Analogy Tell Us About Artificial Consciousness?

arXiv:2610.01002v1 Announce Type: new Abstract: Who or what is conscious? Because subjective experience is directly accessible only in the first person, judgments about consciousness in other entities

What Does a Skill Actually Do? Estimands and Evaluation Validity for Tool and Skill Use in LLM Agents: A Critical Review

arXiv:2609.33153v2 Announce Type: replace-cross Abstract: Reported improvements from tools and reusable skills in large language model agents refer to different comparisons. This critical narrative re

What Makes Something Hard(er)? Explaining Question Difficulty in Natural Language

arXiv:2610.01627v1 Announce Type: cross Abstract: Difficulty is one of the most fundamental properties of a question: it determines whether the question can meaningfully discriminate between models of

When Do Attention-Head Ablations Support Causal Claims? Projection-Level Confounds, Floor Effects, and Matched Controls

arXiv:2610.00373v1 Announce Type: new Abstract: Attention-head ablation, zeroing a head and measuring the resulting change in task performance, is a common method for inferring which components of a l

When Does Exercise-Specific Joint Selection Help? An Audit of Evaluation and Control Design

arXiv:2610.01188v1 Announce Type: new Abstract: Exercise-specific joint selection can improve skeleton-based correctness classification, but what does that gain establish? We audit 1,057 repetitions f

When More Data Is Not Enough: The Context-Sufficiency Frontier in Generative AI Personalization

arXiv:2610.00654v1 Announce Type: new Abstract: Personalization has long relied on customer data to infer what an individual is likely to value. We call this customer evidence: the customer's historic

When Text-to-Image Helps Editing: The Effects of Conditioning During Denoising

arXiv:2610.01681v1 Announce Type: new Abstract: Unified models are trained for both instruction-based image editing and text-to-image (T2I) generation, but standard editing pipelines keep source-image

When the AI Leaves the Tailorshop: Measuring What an LLM Advisor Leaves Behind in Complex Problem Solving

arXiv:2610.00163v1 Announce Type: cross Abstract: Complex problem solving depends on acting effectively and understanding how a system works. AI advice may support these outcomes unequally. Two prereg

Which LLM to pick? Online Active Model Selection for Large Language Models

arXiv:2610.01592v1 Announce Type: cross Abstract: Large Language Models (LLMs) are increasingly applied to process streaming data, with practitioners relying on benchmarks to select the best model eve

WIPSNet: Deep Learning for Paediatric Wheeze Detection from Overnight Impedance Pneumography

arXiv:2610.00398v1 Announce Type: new Abstract: Overnight impedance pneumography (IP) is used to monitor paediatric respiratory health. Its current clinical readout, the Expiratory Variability Index (

XOR-Trellis: Ultra-Low-Complexity Dequantization and Curvature-Aware Hadamard-Free LLM Quantization

arXiv:2610.00432v1 Announce Type: cross Abstract: Trellis-coded quantization enables high-dimensional compression of large language model (LLM) weights at ultra-low bit widths without the exponentiall

Zero Flux: Flow-Based Comparison of High-Dimensional Discrete Distributions

arXiv:2610.01472v1 Announce Type: cross Abstract: Comparing two high-dimensional discrete distributions has always been a challenging task due to the exponentially growing state space and complex chan

A Data-Free Physics-Informed Neural Operator for Level-Set Interface Advection

arXiv:2609.38195v1 Announce Type: new Abstract: Operators for interfacial problems are trained on reference solutions produced by the solver they are intended to replace. This work develops a data-fre

A differentiability framework for zigzag persistent homology via linear interpolation

arXiv:2609.39242v1 Announce Type: new Abstract: Persistent homology can be differentiated and incorporated into learning pipelines, but no analogous framework exists for zigzag persistence, which is n

A Flow Matching Algorithm for Many-Shot Adaptation to Unseen Distributions

arXiv:2605.06272v2 Announce Type: replace Abstract: While generative modeling has achieved remarkable success on tasks like natural language-conditioned image generation, enabling model adaptation fro

A Generalisation Signal Need Not Be a Model-Selection Signal

arXiv:2609.39099v1 Announce Type: cross Abstract: Model selection in computational biology often relies on validation data drawn from the training regime, even when deployment lies outside it. When va

A Generalizable and Explainable Framework for Synthetic Video Detection Using First-Digit Gradient Statistics

arXiv:2609.39585v1 Announce Type: new Abstract: AI video generators have not only become harder to detect but are used to generate a diverse set of scenarios from landscapes to street views to animal

A library for differentiable signal processing and machine learning on the sphere

arXiv:2609.39737v1 Announce Type: new Abstract: The two-dimensional sphere embedded in three-dimensional Euclidean space S2, plays a central role in a variety of scientific and engineering domains, in

A Moving-Horizon Approximate Branch-and-Reduce Method for Deep Classification Trees

arXiv:2609.38194v1 Announce Type: cross Abstract: Despite the importance for interpretability, decision trees face severe scalability challenges. Existing global optimal methods are often limited by b

A polynomial time algebraic solution to exact marginal inference in Markov Random Field models

arXiv:1709.09051v3 Announce Type: replace-cross Abstract: This paper develops on algebraic grounds a polynomial time exact linear solution to the hard combinatorial problem of marginal inference in Ma