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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

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People really hate AI, so why can’t they get enough?

DGX agent

Over the summer I talked to the CEO of Springboards, a startup building an LLM that’s designed to come up with a wider variety of responses than its mainstream rivals do. At the start of the call, he

researchmit-tech-review

5 Oct 2026

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

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

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

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

Power-SMC: Low-Latency Sequence-Level Power Sampling for Training-Free LLM Reasoning

arXiv:2602.10273v3 Announce Type: replace-cross Abstract: Reasoning ability in large language models is often attributed to distribution sharpening: concentrating output probability on high-likelihood

Predicting and Repairing Merge Collapse in Large Language Models

arXiv:2610.03199v1 Announce Type: cross Abstract: Large language models fine-tuned from a shared base can be merged by averaging their task vectors, but some merges collapse far below the base model,

Predicting Steering Vectors and Adapter Weights for Few-Shot Author-Style Transfer

arXiv:2610.03163v1 Announce Type: cross Abstract: Adapting large language models to an individual author's style from a few examples is challenging, and scientific writing sharpens the difficulty: for

Predictively Oriented Gaussian Process Posteriors

arXiv:2610.03201v1 Announce Type: cross Abstract: Gaussian Processes (GPs) are a powerful tool for modelling and quantifying uncertainty in functional relationships. However, they require practitioner

Preserving Anatomical Continuity: Three-Stage Pipeline for Colon Segmentation in 3D Abdominal CT Scans

arXiv:2610.03467v1 Announce Type: cross Abstract: Accurate colon segmentation from CT images is essential for colorectal disease analysis, yet deep learning based methods often produce disconnected pr

Preserving Mathematical Reasoning in Compressed Diffusion Language Models via Trajectory-Aware Low-Rank Approximation

arXiv:2610.03326v1 Announce Type: new Abstract: Diffusion language model (dLLM) compression faces a known challenge because calibration is typically performed on clean, fully visible activations, wher

ProgressNet: Sketching and Prompting with a Frozen Text-to-Image Model

arXiv:2610.03512v1 Announce Type: new Abstract: Humans draw progressively: a few strokes, a look at the result, a stroke erased, a prompt revised. Image generators do not work this way. They typically

Psi-Resilience: Model-Free Feature Importance from 1D Topological Signals

arXiv:2610.02299v1 Announce Type: cross Abstract: We introduce Psi-Resilience, a model-free feature importance method that derives explanations directly from the data itself via 1D topological signals

Quantifying the Value of Constructive Induction, Knowledge, and Noise Filtering on Inductive Learning

arXiv:2610.02615v1 Announce Type: new Abstract: Learning research, as one of its central goals, tries to measure, model, and understand how learning-problem properties affect average-case learning per

Rank-Aware Speculative Sampling for Diffusion Draft Trees

arXiv:2610.02251v1 Announce Type: new Abstract: Speculative sampling accelerates diffusion generation by verifying inexpensive draft states in parallel while preserving the target law. Recent tree-bas

RAOA: Alternating-Operator Neural Computation with Programmable Radio Propagation

arXiv:2610.02683v1 Announce Type: new Abstract: Can programmable radio propagation serve as computational depth rather than only as a communication channel or one-shot analog transform? We introduce t

RASPER: Reward-Aligned Summarization of Clinical Notes for EHR Outcome Prediction

arXiv:2610.02979v1 Announce Type: new Abstract: Unstructured discharge notes in Electronic Health Records (EHRs) often carry signal complementary to structured medical codes, holding patient-specific

Real-time Event-camera Stereo Visual Odometry via Keytime Gaussian Process Regression

arXiv:2610.02601v1 Announce Type: new Abstract: Event cameras have microsecond-level temporal resolution and high dynamic range which make them more resilient to motion blur and poor illumination than

researcharxiv-cs-ro

Real-Time sEMG-Based Telecontrol of an Assistive Robotic Arm Using a 1D Convolutional Neural Network

arXiv:2607.16310v2 Announce Type: replace Abstract: Motor impairments affecting the upper limb significantly reduce autonomy in daily activities, particularly for tasks involving object manipulation.

researcharxiv-cs-ro

Recursive Harness Self-Improvement for Frontier Reasoning Data Synthesis

arXiv:2610.03548v1 Announce Type: new Abstract: Generating progressively harder reasoning problems requires synthesis procedures that adapt as the task distribution evolves. Existing task-level recurs

Recursive Self-Improvement in Unified Multimodal Models

arXiv:2610.03002v1 Announce Type: new Abstract: Unified multimodal models (UMMs) understand and generate both text and images, which lets a model produce its own training data. Existing self-improveme

Refinement Buys Intelligibility, Search Buys Identity: What Test-Time Compute Buys in Masked-Diffusion TTS

arXiv:2610.03320v1 Announce Type: new Abstract: Diffusion language models for text-to-speech combine two forms of computation: model depth (parameters) and refinement steps (inference budget). We ask

Relevant Evidence Decoding for Audio-Visual Hallucination Mitigation

arXiv:2610.02976v1 Announce Type: new Abstract: Audio-Visual Large Language Models (AV-LLMs) remain prone to cross-modal hallucinations, where one modality incorrectly affects predictions about anothe

Reliability of Probabilistic Emulation of Physical Systems

arXiv:2606.12997v2 Announce Type: replace Abstract: Two dominant approaches have emerged for generating probabilistic forecasts of physical systems: generative models, such as diffusion or flow matchi

Rethinking Epistemic Uncertainty in Node Classification through Information Growth

arXiv:2610.03418v1 Announce Type: cross Abstract: Epistemic uncertainty should decrease as additional information about the data-generating process (DGP) becomes available to the predictor. Yet, exist

Rethinking Fixed Temporal Grids: Frequency-Disentangled Motion Generation

arXiv:2610.03012v1 Announce Type: new Abstract: Most human motion generation methods encode motion as tokens on a uniform temporal grid, where every token spans the same fixed time window. Human motio

Rethinking What to Cache in Few-Step Diffusion Transformers: Solver-Aware Target Selection

arXiv:2610.03577v1 Announce Type: cross Abstract: Diffusion Transformers (DiTs) can generate high-quality images and videos, but generating each sample requires multiple costly DiT forward passes. Two

Revisiting Input Time-frequency Representations in Multi-pitch Estimation for Vocal Ensembles

arXiv:2610.03656v1 Announce Type: cross Abstract: Multi-pitch estimation in vocal ensembles is challenging because singers occupy overlapping pitch ranges and often sing at closely spaced fundamental

Robust Adversarial Quantification via Conflict-Aware Evidential Deep Learning

arXiv:2506.05937v3 Announce Type: replace-cross Abstract: Reliability of deep learning models is critical for deployment in high-stakes applications, where out-of-distribution or adversarial inputs ma

RT-SFT: Text Style Transfer from Non-Parallel Corpora by Roundtrip Translation

arXiv:2602.15013v2 Announce Type: replace Abstract: Text style transfer (TST) is naturally a supervised task - rewrite a sentence in a target style while preserving its meaning - yet the parallel corp

RUL-Aware RRT*: Degradation-Balanced Motion Planning for Robotic Manipulators

arXiv:2610.02469v1 Announce Type: new Abstract: Robotic manipulators operating over long durations often experience uneven joint degradation, which causes the weakest actuator to fail prematurely, lea

researcharxiv-cs-ro

RYOPO: Bringing End-to-End Category-Level Object Pose Estimation into Real Time

arXiv:2610.03013v1 Announce Type: new Abstract: Category-level object pose estimation predicts the rotation, translation, and metric size of unseen instances within known categories. Many accurate RGB

S^{2}-PINN: Stochastic Separable Physics-Informed Neural Networks

arXiv:2610.03303v1 Announce Type: new Abstract: Uncertainty quantification (UQ) for random partial differential equations (PDEs) is ubiquitous in computational science and engineering. However, classi

S2S-JEPA: Predicting the Predictable at Subseasonal-to-Seasonal Timescales

arXiv:2610.03106v1 Announce Type: cross Abstract: The subseasonal-to-seasonal (S2S) timescale, roughly from two weeks to two months ahead, is a critical forecast window for sectors such as agriculture

SCOPE-4D: Endoscopic 4D Geometry Foundation Models

arXiv:2610.02343v1 Announce Type: new Abstract: Geometric understanding supports endoscopic navigation and robotic assistance, but learning reliable endoscopic geometry faces two challenges: scarce ge

SEDIMA: Cross-Run Hierarchical Insight Memory for Evolutionary Search Agents

arXiv:2610.02361v1 Announce Type: cross Abstract: Large language model (LLM)-driven evolutionary search is a powerful paradigm for automated program and algorithm discovery, yet existing systems are l

Shrome at Touche: Soft-Vote Ensembling and Counter-Causal Augmentation for Causality Extraction

arXiv:2610.03268v1 Announce Type: new Abstract: Touche 2026 extends causality extraction to counter-causal claims: news sentences whose surface form appears causal but whose meaning denies the causati

SigLIP2 for aerial fire risk classification

arXiv:2610.03689v1 Announce Type: new Abstract: We examine the transfer of a pretrained SigLIP2 image encoder to seven class fire risk classification from aerial imagery. We introduce a reproducible p

Signal Simplification Is Not Predictive Simplification: Diagnosing Residual Neural Forecasting in Short-Horizon Volatility

arXiv:2610.03019v1 Announce Type: new Abstract: Hybrid statistical-neural pipelines often assume that a successful statistical first stage leaves a cleaner and more learnable residual target. We exami

Simulation-Free Learning of Population Dynamics with Wasserstein Lagrangian Residuals

arXiv:2610.03679v1 Announce Type: new Abstract: The dynamics of cells, organisms, and fluids are often modeled as probability distributions evolving over time. Reconstructing and extrapolating this ev

Single-Pass Uncertainty Heads for Claim-Level Hallucination Detection in Persian Medical Language Models

arXiv:2610.03482v1 Announce Type: new Abstract: Hallucination detection is particularly important for medical language models, but repeated-sampling approaches are expensive and existing uncertainty-h

SlimKV: Joint Token-Feature KV Cache Compression with Reconstruction-Free Beacon Attention

arXiv:2610.02953v1 Announce Type: new Abstract: Long-context LLM serving is increasingly bottlenecked by KV-cache memory, especially in resource-constrained scenarios. Among existing KV-cache compress

SoTa: Soft Tactile Skins for Dexterous Manipulation

arXiv:2610.02338v1 Announce Type: cross Abstract: A growing body of work suggests that tactile sensing gives robot policies contact information that complements vision in dexterous manipulation. Howev

Spatial Memory Intelligence: Endowing World Models with Understanding-Driven Long-Term Memory

arXiv:2610.02521v1 Announce Type: new Abstract: Long-video generation and world models have shown strong potential for interactive entertainment and embodied simulation by predicting future observatio

SPEAR: A Spectral-Disentangled MoE Neural Operator with Knowledge-Guided Expert Aggregation for Large-Scale PDE Pretraining

arXiv:2610.03265v1 Announce Type: cross Abstract: Large-scale pre-training has improved the generalization of neural operators across diverse PDEs. However, existing PDE foundation models still strugg

SpectralCache: Accelerating Diffusion-Based World Models via Spectral Feature Caching

arXiv:2610.02660v1 Announce Type: new Abstract: Diffusion-based world models enable high-quality interactive environment generation but suffer from substantial inference overhead due to repeated Trans

StanceEval 2026: The Second Stance Detection Shared Task

arXiv:2610.03215v1 Announce Type: new Abstract: StanceEval 2026 is the second edition of the StanceEval shared task series on stance detection in Arabic social media text. Stance detection aims to ide