Search: “research”

Beyond Pairwise Repulsion: Collective Diversity via Determinant Maximization in Diffusion Sampling

arXiv:2610.22267v1 Announce Type: new Abstract: Strong guidance in text-to-image (T2I) diffusion models concentrates sampling toward high-density modes of the conditional distribution, collapsing inde

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Beyond the Dominant Label: Recovering Coexisting Lesion Evidence with Multiple Instance Learning

DGX agent

arXiv:2610.22091v1 Announce Type: new Abstract: Whole-slide images may contain coexisting lesions, yet weak supervision typically provides only the most severe diagnosis. We formulate this setting as

researcharxiv-cs-cv

16 Oct 2026

Bridging the Markerless Tracking Validation Gap: Intraoperative X-ray Workflow Integration

arXiv:2610.21696v1 Announce Type: new Abstract: Markerless intraoperative tracking of spinal anatomy via RGB-D sensors is a promising alternative to invasive bone-anchored fiducials, yet no existing c

Can LLMs Anticipate Their Cruxes?

arXiv:2610.21006v1 Announce Type: new Abstract: To use language models to help us make decisions we would like to understand the rationale behind the language model's outputs. In principle, the langua

Causal Analysis of Robot Foundation Models Enables Efficiency Gains

arXiv:2610.20750v1 Announce Type: new Abstract: Vision-language-action (VLA) models are a promising approach to general purpose robot manipulation. While the internal computation of vision-language mo

researcharxiv-cs-ro

Causal Syntax Circuits in CodeLMs: Budget and Probe Decide What Looks Localised

arXiv:2610.20683v1 Announce Type: new Abstract: Code models write Python when the prompt does not say which language to use. We ask a mechanistic question about that habit: is it produced by a small,

CausalEvo: Causal Skill Self-Evolution for Health LLM Agents

arXiv:2610.21016v1 Announce Type: new Abstract: Large language model (LLM) agents for health can accumulate reusable textual skills from task feedback, such as calculation criteria, measurement time p

CBF-Based Control Allocation for Omnidirectional Tiltrotor Aerial Robots

arXiv:2610.22057v1 Announce Type: new Abstract: Actively tilting aerial robots can generate six-dimensional wrenches, but slow servo response can make a desired wrench infeasible during reconfiguratio

researcharxiv-cs-ro

Change the Number, Change the Answer: Assessing Rating Scale Sensitivity in LLM-Based Text Scoring

arXiv:2610.22187v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly used in computational social science to assign scalar scores to social and psychological constructs. How

CLAD: Keypoint Matching Using Global Line Correspondences

arXiv:2610.21409v1 Announce Type: new Abstract: Traditional keypoint descriptors, such as SIFT (Scale-Invariant Feature Transform) and ORB (Oriented FAST and Rotated BRIEF), are computed from local im

Classical methods for modern applications: synthetic tabular data generation using lightweight discrete response continuous latent variable model

arXiv:2610.21674v1 Announce Type: new Abstract: In this paper, we present a lightweight algorithm for modelling tabular data containing both continuous and discrete variables. The method uses empirica

Clean Data Can Still Carry Backdoors: Support-Persistent Backdoors for Model Reuse

arXiv:2610.21208v1 Announce Type: cross Abstract: Traditional backdoor attacks inject artificial trigger patterns into training data, causing models to misclassify triggered inputs while maintaining n

Co2In: a Bi-level Memory Incremental Learning Framework with Knowledge Encoding, Consolidation, and Integration

arXiv:2610.21804v1 Announce Type: new Abstract: Incremental learning (IL) aims to continually acquire new knowledge (plasticity) while retaining previously learned information (stability). However, st

CoDeFont: One-Shot Font Generation via Multi-Scale Factor-Specific Representation Learning

arXiv:2610.21364v1 Announce Type: new Abstract: One-shot Font Generation (OFG) aims to synthesize a target glyph by transferring the stylistic characteristics of a single reference glyph while preserv

Compiling Multi-Threshold Operators for Quantized Non-Monotonic and Fine-Granular Activations in Custom-Tailored DNN Accelerators

arXiv:2610.21825v1 Announce Type: cross Abstract: Aggressive quantization of neural networks can expose activation functions as bottlenecks for efficient hardware acceleration. Implementing quantized

Computational and Statistical Hardness of Calibration Distance

arXiv:2603.18391v2 Announce Type: replace-cross Abstract: The distance from calibration, introduced by B{l}asiok, Gopalan, Hu, and Nakkiran (STOC 2023), has recently emerged as a central measure of mi

Conditional Mean Flows: Few-Step Densities for Simulation-Based Inference

arXiv:2610.21657v1 Announce Type: cross Abstract: Flow matching has emerged as a powerful generative family for simulation-based inference (SBI). However, sampling and density evaluation require numer

CoSTA: Compressed Speech Token Adaptation for Efficient Spoken Dialogue Models

arXiv:2610.21143v1 Announce Type: cross Abstract: Spoken Dialogue Models (SDMs) typically share a speech-token space for generation and synthesis, leading to long autoregressive sequences and costly i

CoTranslator: Reverse to Forward Chain-of-Thought Translator for Reasoning Distillation

arXiv:2610.20828v1 Announce Type: cross Abstract: Reasoning distillation requires chain-of-thought (CoT) data with correct answers, but obtaining such data efficiently remains challenging. Forward CoT

CoTS: Competitive Token Selection for Latent Reasoning in Large Language Models

arXiv:2610.20642v1 Announce Type: cross Abstract: Recent latent reasoning methods move beyond discrete Chain-of-Thought (CoT) by replacing sampled tokens with continuous soft embeddings or hidden stat

CoViG: Coarsened Vision GNN for Image Classification

arXiv:2610.21321v1 Announce Type: new Abstract: Although Graph Neural Networks are widely used in various domains, they remained mostly unexplored in computer vision. Convolutional Neural Networks and

Cross-Prompt Inference Mitigates Rare-Class Suppression in Imbalanced VLM Finetuning

arXiv:2610.21470v1 Announce Type: new Abstract: When a vision-language model is finetuned on class-imbalanced data, rare-class recall can fall well below the model's own zero-shot performance. In this

Deep Learning of Topological Equivalence Classes

arXiv:2610.21981v1 Announce Type: cross Abstract: We demonstrate an application of deep learning to the problem of identifying whether two generating vectors correspond to topologically equivalent fin

Defining and Generating Compositional Structure

arXiv:2610.20922v1 Announce Type: new Abstract: Compositional structure is pervasive in nature and across scales: atoms combine into molecules, molecules into cells, and cells into organisms, while fu

Denoising Score Matching in Diffusion Models: The Effect of Rank Constraints on Generalization

arXiv:2610.20850v1 Announce Type: new Abstract: Architectural biases restrict the class of functions that a diffusion score network can represent, but their effect on generalization remains poorly und

Denoising Textures is a Different Ballgame Altogether!

arXiv:2610.22258v1 Announce Type: cross Abstract: The human brain effortlessly deciphers colors and textures from visual stimuli and reconstructs the world around us, yet preserving such details remai

Dense4D: Pixel-Level 4D Human Correspondence

arXiv:2610.22325v1 Announce Type: new Abstract: Reconstructing human motion in 4D requires identifying the same surface points through articulation, deformation and changes in visibility. We introduce

Designing Transformers for Continuous Diffusion Language Models

arXiv:2610.22330v1 Announce Type: new Abstract: Continuous diffusion language models (CDLMs) offer an alternative approach to parallel language generation; however, most existing studies directly use

DIAL: Dynamic and Informed Adjustment of the Native Stochastic Law for Reliable Weather Ensembles

arXiv:2610.21639v1 Announce Type: new Abstract: Ensemble weather forecasts can look reliable in global averages while hiding too little spread in some cases and too much in others. These errors vary a

Diffusion Language Models as Open Quantum Systems

arXiv:2610.21672v1 Announce Type: cross Abstract: Diffusion language models generate text by reversing a classical diffusion process over token sequences. We show that their continuous-time forward an

Discovering state-of-the-art quantum circuits with large language models

arXiv:2610.22367v1 Announce Type: cross Abstract: Significant efforts are currently being directed toward the implementation of large-scale quantum information processors, but realizing useful quantum

DK-VLM: Geometry as Position for Spatial Reasoning in Vision-Language Models

arXiv:2610.22356v1 Announce Type: new Abstract: Vision-language models still struggle to understand 3D spatial relations across views and update spatial judgments as the observer moves. A common appro

Does Latent Chain-of-Thought Actually Reason? A Single, Unifying Taxonomy for Latent Reasoning

arXiv:2610.21182v1 Announce Type: new Abstract: Latent chain-of-thought replaces written reasoning steps with continuous hidden states, giving models additional steps to compute before answering. It r

Does Morphological Correctness Matter for Tokenization? A Scrambled Control Study in Tagalog

arXiv:2610.20859v1 Announce Type: new Abstract: Typology-aware tokenizers are motivated by the claim that segmentation which respects morpheme boundaries preserves information that frequency-driven se

DPA-MoE: A Runtime Precision Control Framework for MoE Inference

arXiv:2610.21378v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models reduce computation by routing each token to a small set of experts, but each selected expert is still used at a fixed pr

DropKV: Decoupling Residual-Output Perturbation for Near-Optimal KV-Cache Eviction

arXiv:2610.22130v1 Announce Type: new Abstract: Key-value (KV) cache management has become a critical bottleneck for scaling Large Language Models (LLMs) to long-context scenarios due to linear memory

DuET: Note-Frame Dual Encoding for Piano Performance-to-Score Transcription

arXiv:2610.21467v1 Announce Type: cross Abstract: Transcribing expressive piano performances into scores requires interpreting individual note timings within an underlying metrical structure. However,

Dynamic ordering in sequence generation in Transformers: experiments on low-resource Tagging scenarios

arXiv:2610.21862v1 Announce Type: new Abstract: This paper introduces TagInsert, a Transformer-based model that challenges the common left-to-right (L2R) generation paradigm in Transformers, for seque

Edit4D: Editable 4D Scene Generation with Textual Control

arXiv:2610.21668v1 Announce Type: new Abstract: We introduce Edit4D, an editable text-to-4D scene generation framework that constructs 4D scenes from separate background and dynamic character represen

Effectiveness of Hidden-State Probes for Localizing Reasoning Failures

arXiv:2610.22046v1 Announce Type: cross Abstract: Verifying the final answer of a long reasoning trace may show that the trace is wrong but it does not distinguish three cases. The problem may lie bey

Efficient Agnostic Learning of Univariate Densities Under Local Differential Privacy

arXiv:2610.21033v1 Announce Type: cross Abstract: We propose a general framework for non-interactive locally differentially private (LDP) learning of structured univariate distributions that can be ap

EliteReplay: Preserving Diverse Solutions in RL Post-Training via Quality-Diversity Search

arXiv:2610.22290v1 Announce Type: new Abstract: Reinforcement learning has become a common post-training technique to improve the accuracy of LLMs on verifiable tasks. However, such training can narro

ESG-Kor: A Korean Dataset for ESG-related Information Extraction and Practical Use Cases

arXiv:2610.21368v1 Announce Type: cross Abstract: With the expansion of pre-trained language model usage in recent years, the importance of datasets for performing tasks in specialized domains has sig

ETH: Data-Balanced Heterogeneous Pipeline Parallelism for Training Large Models

arXiv:2610.22035v1 Announce Type: cross Abstract: Current heterogeneity-aware training systems for large models balance workloads by assigning unequal numbers of layers across pipeline stages, a strat

Expanding Attention: A Taylor-Series Route to Linear-Time Transformers with a Fixed Number of Recurrent States

arXiv:2610.20637v1 Announce Type: new Abstract: We expand the exponential kernel of attention into a truncated Taylor series of n terms and factorize each term into a tensor-power inner product, which

Exploring the Design Space of Permutation Diffusion LLMs

arXiv:2610.20635v1 Announce Type: cross Abstract: Permutation generation with language models requires both text-conditioned ranking and a global one-to-one assignment between candidates and output po

Feature-preserving Latent-EnKF for Data Assimilation of Flows with Shocks

arXiv:2606.12559v2 Announce Type: replace-cross Abstract: The ensemble Kalman filter (EnKF) is widely adopted for sequential data assimilation, but fails for solutions with discontinuities, such as sh

Federated Art Chase: Privacy Leakage and Data Poisoning in Federated Fine-Tuning

arXiv:2610.21547v1 Announce Type: new Abstract: Federated learning (FL) is increasingly used to adapt a pretrained, centrally fine-tuned model to data that remain on user devices, beyond training a mo