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Bridging the Confidence Gap: Temperature Scaling for Calibrating Test-Time Prompt Tuning

arXiv:2609.17386v1 Announce Type: new Abstract: Test-time prompt tuning (TPT) enables adaptation on a single test instance, achieving improved accuracy but often sacrificing calibration performance. M

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Bridging the Gap Between Homogeneous and Heterogeneous Asynchronous Optimization Is Surprisingly Difficult

DGX agent

arXiv:2609.17483v1 Announce Type: cross Abstract: Modern large-scale machine learning tasks often require multiple workers, devices, CPUs, or GPUs to compute stochastic gradients in parallel and async

researcharxiv-cs-lg

16 Sept 2026

CAD-Based Relation Learning and Geometric-Symbolic Planning for Robotic Assembly

arXiv:2609.17263v1 Announce Type: new Abstract: Assembly Sequence Planning (ASP) remains a challenging problem due to its combinatorial nature, making exhaustive planning approaches impractical for co

researcharxiv-cs-ro

Can Deep Learning Achieve Cross-Physics Mapping?

arXiv:2609.16853v1 Announce Type: new Abstract: Can deep learning translate physical fields governed by fundamentally different equations? We address this question by introducing Cross-Physics Mapping

CareMirror: Bringing Caregiver Wellbeing into the Dementia Care Ecosystem

arXiv:2609.17434v1 Announce Type: cross Abstract: Family caregivers of people living with dementia shoulder emotional and practical responsibilities, yet their own wellbeing often remains peripheral t

Cascade: Hierarchical Recoverability Control for Large Language Model Unlearning

arXiv:2609.16890v1 Announce Type: new Abstract: Large Language Model (LLM) unlearning is essential for removing sensitive or copyrighted knowledge while preserving general utility. Existing methods of

Causal Discovery via Transformed Low-Rank Quantile Surfaces

arXiv:2609.16931v1 Announce Type: cross Abstract: We propose Low-Rank Quantile Surfaces (LRQS), a bivariate causal model in which, in the causal direction, an unknown monotone transformation of the co

Causal neural set filtering for online multi-target tracking

arXiv:2609.16054v1 Announce Type: cross Abstract: Transformer-based multi-target tracking (MTT) jointly learns data association and state estimation, but MT3/Track-MT3-style trackers repeatedly re-enc

Challenges of Auditing: Variability in Outputs of Large Language Models for Health

arXiv:2609.16590v1 Announce Type: new Abstract: People increasingly use frontier AI models for health advice, but via different access modes (e.g., ChatGPT, ChatGPT Health, APIs) with varying settings

Channel-Informed Neural Network for Physical Layer Key Generation

arXiv:2609.16341v1 Announce Type: new Abstract: Physical-layer key generation (PKG) enables wireless devices to establish shared keys from reciprocal channel observations without directly exchanging t

Channel-Wise and Token-Aware Post-Training Quantization for Visual State Space Duality

arXiv:2609.16656v1 Announce Type: new Abstract: State space models (SSMs), particularly Mamba, have emerged as efficient alternatives to attention-based architectures and have been extended to vision

CineScale: Tuning-Free High-Resolution Video Generation

arXiv:2508.15774v2 Announce Type: replace Abstract: Visual diffusion models achieve remarkable progress, yet they are typically trained at limited resolutions due to the lack of high-resolution data a

CLASH: Counterfactual Auditing of Lexical and Prosodic Reliance in Spoken Sarcasm Detection

arXiv:2609.16582v1 Announce Type: cross Abstract: Spoken sarcasm detectors may exploit lexical content, prosody, or their interaction, yet conventional evaluation cannot reveal which cues drive their

Closing the Loop: Branch-and-Bound for Scalable Verification of Nonlinear Neural Feedback Systems

arXiv:2609.16298v1 Announce Type: new Abstract: Despite recent advances in the verification of nonlinear neural feedback systems, scalability remains the central obstacle, as state-of-the-art solvers

Collision-Aware Humanoid Whole-Body Control under Imperfect Tracking Targets

arXiv:2609.16405v1 Announce Type: new Abstract: Humanoid robots often execute motion commands through whole-body controllers (WBCs) that track targets while maintaining balance and stability. However,

researcharxiv-cs-ro

Comparative Characterization of KV Cache Management Strategies for LLM Inference

arXiv:2604.05012v2 Announce Type: replace-cross Abstract: Efficient inference with Large Language Models (LLMs) increasingly relies on Key-Value (KV) caches to store previously computed key and value

Compute-Optimal Pretrain--Fine-tune in Ridge Gradient Descent

arXiv:2609.16262v1 Announce Type: cross Abstract: Pretraining followed by fine-tuning introduces a compute-allocation problem: under a fixed training budget, compute spent improving the upstream objec

Conditioning noise is a free regularizer for LoRA fine-tuning: no pathology encoder required for diffusion-based artifact detection in histopathology

arXiv:2609.16032v1 Announce Type: cross Abstract: Diffusion-based artifact detectors score whole-slide image patches by reconstruction error under a model fine-tuned on clean tissue. We show that cond

ConGraspXL: Controllable Constraint-Conditioned Dexterous Grasping Motion Synthesis

arXiv:2609.16319v1 Announce Type: cross Abstract: Dexterous grasping is usually conducted for specific tasks, leading to heterogeneous constraints such as specific approach directions, desired contact

Constant Swap Regret in General-Sum Games via Optimistic Transition Matrices

arXiv:2609.16751v1 Announce Type: cross Abstract: We give deterministic and uncoupled learning dynamics for finite multiplayer general-sum games under full-information feedback that achieve constant i

Copula Adapted Directed Acyclic Graph for Cluster Representation of Biomedical Data

arXiv:2609.16240v1 Announce Type: cross Abstract: Diagnostic errors and mislabeling are common in biomedicine, which compromise the reliability of predictive models and data-driven outcomes. Stratifyi

Cross-Domain Inference for Human Localization: Applying Wi-Fi RSSI Data to CSI-Trained Models

arXiv:2609.17204v1 Announce Type: cross Abstract: Wi-Fi signal data can be used to compromise the privacy of individuals. While many existing approaches rely on Channel State Information (CSI), collec

CTAN: Cycle-Temporal Attention Network for Embodied Audio-Visual Navigation

arXiv:2609.17420v1 Announce Type: cross Abstract: Audio-visual embodied navigation equips robots with the capability to infer the locations of sound sources by integrating visual inputs and acoustic i

Decentralized Gossip Learning and Federated Averaging for Histopathology Image Classification

arXiv:2609.16448v1 Announce Type: new Abstract: Breast histopathology analysis increasingly relies on distributed learning because direct data pooling across institutions is often restricted by privac

DecoGS: Adaptive Static-Dynamic Decoupling of 3D Gaussians for Free-Viewpoint Video Streaming

arXiv:2609.17230v1 Announce Type: new Abstract: Streaming 3D reconstruction demands both speed and temporal fidelity, goals that existing methods undermine by updating every Gaussian every frame, even

Deconstructing Stereotypes: Scope-Conditioned Generation for Effective Multilingual Counterspeech

arXiv:2609.16906v1 Announce Type: new Abstract: Counterspeech (CS) - direct responses that counter online Hate Speech (HS) using reasoning and alternative viewpoints - has emerged as an alternative to

Diagnosing the Fact-Grounding Gap in Multi-Hop Question Answering

arXiv:2609.17043v1 Announce Type: cross Abstract: Multi-hop question answering requires combining information from multiple documents to answer complex questions. These systems have grown increasingly

DiaWhisper-DPO: Role-Attributed Transcription of Clinical Interviews via Failure-Mined Preference Optimization

arXiv:2609.16661v1 Announce Type: new Abstract: Automated depression screening from clinical interviews requires attribution of utterances to the clinician or patient. We evaluate two datasets: DAIC-W

Differentiable Mesh State Estimation via Factor Graph Inference for Deformable Object Reconstruction

arXiv:2609.16686v1 Announce Type: cross Abstract: Estimating deformable object states remains a fundamental challenge in robotics and simulation. We propose a novel factor graph-based framework for pr

Digital Persuasion: Understanding the Impact of Online Influencers on Public Opinion

arXiv:2609.16062v1 Announce Type: cross Abstract: The studying of opinion dynamics and its propagation within social networks is crucial for addressing a wide range of challenges, including political

Disrupted Companionship: A Risk Assessment Framework and Cross-Platform Quantitative Analysis of Psychosocial Responses to AI Companion Disruptions

arXiv:2609.16907v1 Announce Type: cross Abstract: AI companions can provide meaningful relationships, yet these relationships remain vulnerable to platform-initiated changes. We study AI companion dis

Distributed JEPA: A Self-Supervised Framework for Energy Forecasting

arXiv:2609.17029v1 Announce Type: cross Abstract: Traditional energy forecasting solutions rely on task-specific supervision and energy asset representations, limiting transferability and the ability

Drift Field Net: Learning Ocean Lagrangian advection fields from in-situ and satellite observations

arXiv:2609.16288v1 Announce Type: new Abstract: The North Pacific Subtropical Gyre (NPSG) is a major accumulation zone for floating plastic debris, resulting from basin-scale convergent ocean circulat

Early-Bird Decoding: Accelerating Diffusion LLMs with Learnable Block Sizes and Parallel Sampling

arXiv:2609.16450v1 Announce Type: cross Abstract: Diffusion large language models (dLLMs) offer a promising parallel decoding paradigm as an alternative to autoregressive generation through iterative

EBL: Efficient Broad Learning for Distributed Adaptive Harmonic Analysis

arXiv:2609.16358v1 Announce Type: cross Abstract: Renewable energy systems and electrified transport have found widespread adoption in recent years. The integration of these non-linear loads, dominate

ECHO: Early-layer Collaborative Hierarchical Orchestration with Bonus Logits in Speculative Decoding

arXiv:2609.17241v1 Announce Type: new Abstract: While draft-model-free speculative decoding offers a promising path to efficient LLM inference, it is frequently constrained by stale draft candidates a

Efficient One-to-Many Translation with Joint Multi-Stream Diffusion

arXiv:2609.16312v1 Announce Type: cross Abstract: One-to-many machine translation (MT) is computationally expensive for autoregressive (AR) systems, which suffer from linear latency scaling with both

Efficient Text-to-Image Generation: An Adaptive Step Schedule Controller for Diffusion Models

arXiv:2609.16572v1 Announce Type: cross Abstract: Text-to-image diffusion models often use a fixed number of denoising steps, balancing time costs and image quality. However, the optimal number of ste

Enhancing Low-resolution Image Representation Through Normalizing Flows

arXiv:2601.06834v2 Announce Type: replace Abstract: Low-resolution image representation can be regarded as a special form of sparse representation that retains only low-frequency information while dis

Equivalence of approximation by networks of single- and multi-spike neurons

arXiv:2603.13478v2 Announce Type: replace-cross Abstract: In a spiking neural network, is it enough for each neuron to spike at most once? In recent work, approximation bounds for spiking neural netwo

evMLP: An Efficient Event-Driven MLP Architecture for Vision

arXiv:2507.01927v3 Announce Type: replace Abstract: While CNNs and ViTs dominate vision architectures, all-MLP models offer a structurally simpler alternative whose patch-independent processing is nat

Excited to announce that the Korean translation of 'Deep Learning with Python (3rd Edition)' by @fchollet and @mattdangerw is published! 🚀 …

researchfrancois-chollet--x

Excited to announce that the Korean translation of 'Deep Learning with Python (3rd Edition)' by @fchollet and @mattdangerw is published! 🚀 Updated for Keras 3, TensorFlow, PyTorch, JAX, and Generative

Explainable Graph-theoretical Machine Learning with Application to Alzheimer's Disease Prediction

arXiv:2503.16286v2 Announce Type: replace Abstract: Dementia affects over 55 million people worldwide, projected to reach 139 million by 2050, with Alzheimer's disease (AD) accounting for 60-70% of ca

FAHCD-Net: Frequency-Adaptive Heatmap-Conditional Diffusion Networks for Robust Facial Landmark Detection

arXiv:2609.16842v1 Announce Type: new Abstract: Facial Landmark Detection(FLD) is a crucial task in various applications and has achieved significant advancements in recent years. However, current FLD

Federated stochastic bilevel optimization with fully first-order gradients

arXiv:2609.16350v1 Announce Type: new Abstract: Federated stochastic bilevel optimization has been actively studied in recent years due to its widespread applications in machine learning. However, mos

FlexEE: Self-Speculative and KV-Compatible Early Exiting for Offloading-Aware LLM Inference

arXiv:2609.17008v1 Announce Type: new Abstract: Large language model (LLM) inference is often constrained by both computation and memory, especially in offloading-based deployments where model weights

Formalized Hopfield Networks and Boltzmann Machines

arXiv:2512.07766v2 Announce Type: replace Abstract: Neural networks are widely used, yet their analysis and verification remain challenging. We present a Lean~4 formalization covering both determinist

FreqSpaNet: Frequency and Spatial Learning of SFPF for Physical Layer Hardware Integrity Detection

arXiv:2609.17491v1 Announce Type: new Abstract: Unauthorized hardware replacement can preserve a wireless device's logical identity while altering its physical implementation, posing a challenge to ha