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Quantifying the Memorization-to-Generalization Transition: Scaling Laws and Phase Structure in Grokking

arXiv:2609.10657v1 Announce Type: cross Abstract: Neural networks trained past memorization frequently undergo a delayed transition to generalization, a phenomenon known as grokking. Despite theoretic

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Quantum State Preparation with the QNN-based SRBB Algorithm

DGX agent

arXiv:2503.13647v2 Announce Type: replace-cross Abstract: In this work, a novel algorithm structured on Lie algebras for the approximate quantum state preparation problem is proposed, addressing a cha

researcharxiv-cs-lg

11 Sept 2026

Quasi-static analysis of passive stability in a novel underactuated multi-finger hand

arXiv:2609.11579v1 Announce Type: new Abstract: Underactuated robotic hands achieve adaptive and robust grasping with a reduced number of actuators, but predicting the stable equilibrium pose of the g

Rapid Learning of Dexterous In-Hand Pen Writing through Real-Time Jacobian Estimation

arXiv:2609.11775v1 Announce Type: new Abstract: Dexterous in-hand manipulation of a grasped object with an anthropomorphic hand is an unsolved frontier for robot dexterity. The contact-richness and hi

Rebalancing Token Importance in Language Models with TF-IDF Weighted Cross-Entropy Loss

arXiv:2609.11029v1 Announce Type: new Abstract: Large language models are typically trained under uniform token weighting, which allows frequent and low-information tokens to dominate learning and can

ReGround: Grounding Reviewer Comments in Multimodal Evidence

arXiv:2609.11460v1 Announce Type: new Abstract: Reviewer comments naturally relate to specific parts of the reviewed paper, yet grounding these comments to the underlying evidence is difficult due to

Relatively Smart II: Tractable or Semi-Supervised Instance-Optimal Learning

arXiv:2609.10886v1 Announce Type: new Abstract: We continue the study of relatively smart learning, introduced by Dughmi and Pour (2026), which asks a supervised learner to compete, marginal by margin

Rethinking Verbalized Confidence for LLM-as-a-Judge: A Compatibility Shift on Post-2025 Proprietary Models

arXiv:2609.10996v1 Announce Type: new Abstract: Verbalized confidence, long dismissed as overconfident, coarse, and prone to round-number clustering, is now the more robust soft-scoring mechanism for

REVA: Reusable Evidence View Aggregation for Context-Efficient RAG Serving

arXiv:2609.11209v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) improves knowledge-intensive large language model (LLM) applications by conditioning generation on retrieved docu

Revisiting Avatar-As-Image: High-Fidelity Registration is All You Need

arXiv:2609.11722v1 Announce Type: new Abstract: The representation of 3D clothed humans as standardized 2D UV texture and displacement maps over an underlying body model has long been studied. This co

RIDE: Relocalization-Informed Depth Estimation with 3D Gaussian Splatting

arXiv:2609.11079v1 Announce Type: new Abstract: Render--match--PnP relocalization establishes correspondences between query image pixels and 3D map points for camera pose recovery, but their potential

Rubric-Aligned Disentangled Evaluation of Human Simultaneous Interpreting

arXiv:2609.11131v1 Announce Type: new Abstract: Human simultaneous interpreting (SI) is commonly assessed with analytic rubrics separating meaning transfer, delivery quality, and temporal synchrony, y

Sakana AI、一部「GPT-6 Astra」「Fable 5.1」超えうたうFugu最新版連携先に「両モデルは含まず」 https://www.itmedia.co.jp/aiplus/article/2609/11/2000001405/

Sakana AI has released an updated version of its “Fugu” platform that exceeds performance metrics in some areas compared to the GPT‑6 Astra and Fable 5.1 models. The update does not integrate these tw

researchdavid-ha--x

SAMV-DUSt3R: Instance-Centric 3D Scene Decoupling from Sparse Multi-Views

arXiv:2609.11279v1 Announce Type: new Abstract: With the rising demand to decouple objects from 3D scenes, we propose SAMV-DUSt3R, an end-to-end model that injects SAM2 2D masks into MV-DUSt3R reconst

Scale-Aware 3D Deep Learning for Robust Brain Metastasis Detection in Multimodal MRI

arXiv:2609.10825v1 Announce Type: cross Abstract: Detecting brain metastases in magnetic resonance imaging (MRI) remains challenging because lesions vary widely in size and appearance, with very small

scDEFT: A deep learning framework for drug-effect prediction and counterfactual reasoning

arXiv:2609.10831v1 Announce Type: cross Abstract: Longitudinal single cell atlases now capture matched pre treatment and post treatment states from responders and non responders, presenting an opportu

Scored vs. Generated Readouts in Behavioral Language Models: An Empirical Study of Elicitation Format

arXiv:2609.09882v1 Announce Type: new Abstract: Language models fine-tuned on customer behavior can predict outcomes and generate explanations, but these readouts are often treated as interchangeable.

Seamless Whole Slide Label-Free Virtual Staining

arXiv:2609.10914v1 Announce Type: cross Abstract: Label-free virtual staining offers a compelling, non-destructive alternative to standard histopathology; however, its clinical adoption is hindered by

SegKAN: High-Resolution Medical Image Segmentation with Long-Distance Dependencies

arXiv:2412.19990v3 Announce Type: replace-cross Abstract: Hepatic vessels in computed tomography scans often suffer from image fragmentation and noise interference, making it difficult to maintain ves

Semi-Tensor Product-Based Multi-Term Randomized T-SVD and Its Visual Applications

arXiv:2609.11168v1 Announce Type: new Abstract: Tensor singular value decomposition (T-SVD), which is built upon the tensor-tensor product (t-product), has emerged as a powerful tool for processing hi

Semidefinite Programming for Quantum Channel Learning

arXiv:2601.12502v2 Announce Type: replace Abstract: The problem of reconstructing a quantum channel from a sample of classical data is considered. When the total fidelity can be represented as a ratio

Seven Sources of Physical AI Capability Formation

arXiv:2609.09627v1 Announce Type: new Abstract: Capabilities relevant to Physical AI can arise from materially different formation histories, yet existing taxonomies organized by morphology, architect

Shifting Relational Paradigms for Affective Computing: Affective Resonance, Vitality Affects, and Vocal Interaction Fields

arXiv:2609.09864v1 Announce Type: new Abstract: Affective computing has largely followed an individual-state paradigm, extracting discrete emotion labels or arousal/valence from isolated speakers. We

Single-Stream Multi-Feature Fusion with Temporal Robustness for Gait Emotion Recognition

arXiv:2609.11680v1 Announce Type: new Abstract: 3D skeleton-based gait emotion recognition faces high annotation costs, data scarcity, and poor generalization on heterogeneous data. This paper propose

Sparsity Regularized and Robust Mean Variance Portfolio Selection Under Ellipsoidal Uncertainty

arXiv:2609.11749v1 Announce Type: cross Abstract: We investigate mean-variance portfolio selection with an ell_0-penalty to promote sparsity in asset allocations. Uncertainty in the mean return vector

SpecGuard: Inference-Time Backdoor Detection For Free

arXiv:2609.11799v1 Announce Type: cross Abstract: Large language models are often fine-tuned, shared, or downloaded from third parties, so a deployed model may carry a hidden backdoor that behaves nor

SSS: Semi-Supervised SAM-2 with Efficient Prompting for Medical Imaging Segmentation

arXiv:2506.08949v2 Announce Type: replace Abstract: In the era of information explosion, efficiently leveraging large-scale unlabeled data while minimizing the reliance on high-quality pixel-level ann

Strategic Type Spaces

arXiv:2606.08297v2 Announce Type: replace-cross Abstract: We provide a strategic foundation for information: in any given game with incomplete information we define strategic quotients as information

Sublinear Variational Optimization of Gaussian Mixture Models with Millions to Billions of Parameters

arXiv:2501.12299v3 Announce Type: replace-cross Abstract: Gaussian Mixture Models (GMMs) range among the most frequently used models in machine learning. However, training large, general GMMs becomes

SWRouter: Similarity-Contractive Window Routing for Multi-Turn Large Language Model Conversations

arXiv:2609.11414v1 Announce Type: new Abstract: Large language models exhibit complementary strengths, motivating routing methods that dispatch each query to the most suitable model. Although existing

TailProp: content-adaptive light- and heavy-tailed propagation for vision

arXiv:2609.11081v1 Announce Type: new Abstract: Science-inspired vision models show that explicit propagation dynamics can provide structured and interpretable alternatives to conventional token mixin

Talking to Itself While Coding: What Makes Comments Help Code Generation?

arXiv:2609.09242v1 Announce Type: cross Abstract: Large Language Models (LLMs) often generate natural-language comments while writing code, and these comments become part of the context used to genera

Temporal and Multimodal Deep Learning for Cyberattack Detection in LEO Satellite Systems

arXiv:2609.10746v1 Announce Type: cross Abstract: The growing reliance on Low-Earth Orbit (LEO) satellite communication systems has increased the need for intelligent methods capable of detecting cybe

Test time training enhances in-context learning of nonlinear functions

arXiv:2509.25741v3 Announce Type: replace-cross Abstract: Test-time training (TTT) enhances model performance by explicitly updating designated parameters prior to each prediction to adapt to the test

The Illusion of Balanced Multimodal Sentiment Analysis: Beyond the Limits of Optimization-Based Methods

arXiv:2609.11247v1 Announce Type: new Abstract: Multimodal Sentiment Analysis (MSA) remains constrained by modality imbalance, yet the field continues to rely on optimization-based balancing methods t

The Last AI Built by Humans: Toward Genuine Recursive Self-Improvement

arXiv:2609.11873v1 Announce Type: cross Abstract: Recursive self-improvement (RSI) enables AI systems to turn experience and feedback into persistent changes that improve both their capabilities and t

The observational partial order of causal structures with latent variables

arXiv:2502.07891v3 Announce Type: replace-cross Abstract: For two causal structures with the same set of visible variables, one is said to observationally dominate the other if the set of distribution

The Semantic Elevation Operator and the Closure of the Undecidable Class under Preservation

arXiv:2609.11326v1 Announce Type: cross Abstract: The undecidability of a program's static semantic properties is governed by Rice's theorem. Self-modifying systems, however, require analysing not whe

The Vibe Shift in Software Engineering: Evaluating AI-Led Conversational Programming for Performance, Cognition, and Responsible Adoption

arXiv:2609.09560v1 Announce Type: cross Abstract: This study evaluates Vibe Coding, an emerging AI-led conversational programming paradigm that enables developers to generate software through natural-

The widening evaluation gap in medical large language model research 2023 to 2026

arXiv:2609.11770v1 Announce Type: new Abstract: Large language models are superseded every few quarters; clinical evidence takes years. We asked whether medical research is keeping pace with the syste

Thompson Sampling for Non-Monotone Convex Ridge Bandits: Monotonicity Is Not Needed for Polynomial Regret

arXiv:2609.10981v1 Announce Type: new Abstract: Bakhtiari, Lattimore and Szepesvari (COLT 2025) proved that Thompson sampling (TS) has Bayesian regret ilde O(d^{5/2}sqrt n) for bandit convex optimisat

Time-Varying Graph Learning with Constraints on Graph Temporal Variation

arXiv:2001.03346v4 Announce Type: replace-cross Abstract: We propose a novel framework for learning time-varying graphs from spatiotemporal measurements. Given an appropriate prior on the temporal beh

Topological Necessities: Mechanism-Invariant Strategic Subgoals for Cross-Embodiment Goal-Conditioned Control

arXiv:2609.11014v1 Announce Type: new Abstract: Long-horizon goal-conditioned reinforcement learning delegates control to a high-level module that proposes subgoals, but existing subgoals are implicit

Toward Interpretable Multimodal Fusion: Heat Conduction Modeling for Hyperspectral and LiDAR Joint Classification

arXiv:2609.11040v1 Announce Type: new Abstract: The fusion of hyperspectral (HS) and Light Detection and Ranging (LiDAR) data plays a crucial role in enhancing land-cover classification by jointly exp

Tri-DehazeGS: Scene--Medium Decoupled Gaussian Splatting with Transmittance-Aware Optimization

arXiv:2609.11223v1 Announce Type: new Abstract: Recovering clean 3D scenes from hazy multi-view images is challenging because haze attenuates scene radiance and introduces atmospheric scattering. Rece

UBone3D: Physics-Rectified Conditional Flow Matching for Anatomical 3D Shape Completion from Ultrasound

arXiv:2609.11506v1 Announce Type: new Abstract: Three-dimensional ultrasound (US) is a safe, radiation-free complementary modality to CT and X-rays for longitudinal monitoring, yet its segmentation-de

UniMPA: A Unified Memory-Prediction-Action Model via Action-Grounded Transition Modeling

arXiv:2609.11875v1 Announce Type: new Abstract: Recent advances in Vision-Language-Action (VLA) models have improved robotic manipulation, yet observation-to-action learning remains limited by a funda

Using Semantic Uncertainty to Estimate Transition Relevance in Turn-taking

arXiv:2609.10934v1 Announce Type: new Abstract: Turn-taking is a fundamental mechanism that governs when interlocutors speak and listen. Although Spoken Dialogue Systems (SDS) exploit a range of lingu