Search: “research”

Hidden relationships in a document-derived property graph: top-k chunk embeddings and inverse-distance weighting over a dynamically evolving ontology

arXiv:2609.00387v1 Announce Type: cross Abstract: Large language models extracting knowledge graphs from text capture only explicitly stated facts, often leaving semantically related entities disconne

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HiLRP: Toward One Trustworthy Explanation for Vision Transformer: Conservation-Valid Attribution via Attention Primitives

DGX agent

arXiv:2609.01282v1 Announce Type: cross Abstract: Vision Transformer (ViT) design has become increasingly diverse, with backbones combining convolutional stems, windowed, linear, or multi-axis attenti

researcharxiv-cs-ai

2 Sept 2026

Hydra: Marker-Free RGB-D Hand-Eye Calibration

arXiv:2504.20584v2 Announce Type: replace-cross Abstract: This work presents an RGB-D imaging-based approach to marker-free hand-eye calibration using a novel implementation of the iterative closest p

Hypotheses-Guided Self Distillation for Continual Personalization

arXiv:2609.00251v1 Announce Type: new Abstract: As people increasingly interact with LLM assistants in daily life, continually adapting to individual preferences has become essential for effective lon

Importance and methods to control, vary, and characterize mud strength for studying locomotion

arXiv:2609.00563v1 Announce Type: cross Abstract: Animals and robots encounter mud at the water-land interface. Like sand, mud can stay solid or flow like a fluid. Unlike sand, the yield strength of m

Inspicio: Open-Vocabulary, LLM-Based Sense Retrieval for Historical Languages

arXiv:2609.00998v1 Announce Type: cross Abstract: Word Sense Disambiguation has advanced rapidly for English and a handful of well-resourced modern languages, but it continues to assume the existence

IntroConformal: Conformal Factuality Guarantees for Large Vision-Language Models via Introspective Signals

arXiv:2609.01375v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved strong multimodal performance, yet ensuring the factual correctness of generated content remains ch

Inverse kinematic solution for generic 3R positional robots using Conformal Geometric Algebra

arXiv:2609.00311v1 Announce Type: new Abstract: The inverse kinematics of generic 3R robots has been investigated through multiple approaches, mainly algebraic methods involving the solution of certai

Inverse Reconstruction of Shock Time Series from Shock Response Spectrum Curves using Machine Learning

arXiv:2603.03229v3 Announce Type: replace Abstract: The shock response spectrum (SRS) is widely used to characterize the response of single-degree-of-freedom (SDOF) systems to transient accelerations.

Investigating Hyperparameter Optimization and Transferability for ES-HyperNEAT: A TPE Approach

arXiv:2609.00449v1 Announce Type: cross Abstract: Neuroevolution of Augmenting Topologies (NEAT) and its advanced version, Evolvable-Substrate HyperNEAT (ES-HyperNEAT), have shown great potential in d

ISO-RAG: Isoperimetric Noise Control for Retrieval-Augmented Generation

arXiv:2609.00513v1 Announce Type: new Abstract: Retrieval-Augmented Generation (RAG) mitigates large language models (LLMs) hallucinations, yet conventional dense retrieval struggles with the complex

Joint Training Is Not Enough: Conditioned Cross-Granularity Training for Multimodal Document Understanding

arXiv:2609.00756v1 Announce Type: new Abstract: The Mutual Reinforcement Effect (MRE) asks whether a fine, span-level and a coarse, document-level task help each other when one model handles both. We

KGFR: A Foundation Retriever for Generalized Knowledge Graph Question Answering

arXiv:2511.04093v2 Announce Type: replace Abstract: Large language models (LLMs) excel at reasoning but struggle with knowledge-intensive questions due to limited context and parametric knowledge. How

KItCAT: Knowledge Injection via Input Corruption for Auto-regressive Training

arXiv:2609.00082v1 Announce Type: cross Abstract: LLMs acquire vast amounts of knowledge during pre-training, but often lack the specialized knowledge needed to answer questions from niche sources suc

Knowledge Distillation During Mid-Training Favors Reasoning over Factual Recall

arXiv:2609.01532v1 Announce Type: new Abstract: Logit-based knowledge distillation (KD) is used to train smaller language models (LMs) via supervision from stronger teachers, but whether its benefits

Lagged Coupling: Internal Representations Become Readable Before They Become Causal

arXiv:2609.01048v1 Announce Type: cross Abstract: Across the full Pythia suite (160M-12B, eight checkpoints, four task families), a linear probe can read a target variable from the residual stream as

Late Transformer Layers Recode Syntax Canonically: Evidence from Greek Scrambling and Cross-Layer Generalisation

arXiv:2609.00416v1 Announce Type: new Abstract: Probing studies have established that syntactic information is decodable in early and middle transformer layers, but what happens to that information in

Latent Recurrent Thoughts: Recurrent Refinement of Proposed Latents for Reasoning with Frozen LLMs

arXiv:2609.01117v1 Announce Type: new Abstract: Chain-of-thought reasoning unfolds in discrete token space: each step is committed as text, errors propagate, and eliciting good traces presupposes trac

Latent-Space No-Arbitrage Geometry of Generative Models for Implied Volatility Surfaces

arXiv:2609.00332v1 Announce Type: cross Abstract: Generative models for implied volatility surfaces must produce outputs that satisfy static no-arbitrage constraints. We study these constraints in lat

LatentPress: Context Compression Beyond Text and Vision

arXiv:2609.01507v1 Announce Type: cross Abstract: Compressed context is usually carried as human-readable text or as rendered images that must be decoded, even when its consumer is a language model. W

Learning Sparse Decision Trees via Transformer Variational Auto-Encoders

arXiv:2609.01430v1 Announce Type: cross Abstract: Decision trees are among the most widely used models in machine learning, largely due to their transparent decision logic, making them well-suited for

Let Confidence Change, Not the Prediction: Prediction-Preserving Repair for Post-hoc Calibration

arXiv:2609.01072v1 Announce Type: cross Abstract: Post-hoc calibration corrects reported confidence, yet a multiclass calibrator can also change the associated top-1 prediction. Accuracy captures only

Lingua Franca or Probing Artifact? Rethinking Latent Language in Multilingual LLMs

arXiv:2609.00155v1 Announce Type: cross Abstract: Latent language identification is often used to argue that multilingual language models route computation through language-specific states, such as En

Local Reference Geometry Residual Augmentation for Imbalanced Time Series Classification

arXiv:2609.00093v1 Announce Type: new Abstract: Imbalanced time series classification is often addressed by changing the training distribution, objective, logits, or final threshold. These interventio

LOOMSUM:Weaving Quantitative and Narrative Evidence for Faithful Long Text-Table Summarization

arXiv:2609.00241v1 Announce Type: new Abstract: Long documents often distribute important information across extensive narrative passages and multiple tables, making faithful summarization particularl

MADS: A Multiview Acoustic Descriptor Set Beyond Standard Spectral Summaries

arXiv:2609.00792v1 Announce Type: cross Abstract: Dominant audio classification pipelines rely either on compact handcrafted summaries or on fixed time-frequency frontends such as log-mel representati

MarUco: A Markerless 6D Pose Estimation Framework for Closed-Loop Control of Surgical Continuum Manipulators

arXiv:2602.16365v2 Announce Type: replace-cross Abstract: Flexible endoscopic continuum manipulators offer high dexterity and access to complex anatomy, but nonlinear hysteresis limits feedforward con

MaskCode: Mask Transformer for Feedback-Assisted Coding With Linear Block Codes

arXiv:2609.00715v1 Announce Type: cross Abstract: Feedback-based coding schemes have demonstrated substantial performance gains over today's open-loop coding schemes. Unfortunately, these gains are us

Measuring Optimal Transport in Transformer Depth

arXiv:2609.00748v1 Announce Type: new Abstract: A transformer carries each token's state from layer to layer, and the whole vocabulary carried together forms a cloud that moves with depth. We ask whet

MegaStyle++: Scaling Image Style Space through Hierarchical Style Definition

arXiv:2609.01423v1 Announce Type: new Abstract: Image style is a highly abstract, human-constructed concept shaped by a range of visual factors and intrinsically entangled with content, yet a unified

Membership Inference in Fine-tuned Diffusion Language Models via Token-level Memorization Asymmetry

arXiv:2609.00873v1 Announce Type: new Abstract: Diffusion language models (DLMs) have recently emerged as an alternative modeling paradigm to autoregressive LMs, offering advantages such as parallel g

MIDR: Enrichment-Augmented Indexing for Multimodal Document Retrieval

arXiv:2609.01316v1 Announce Type: cross Abstract: Retrieval over visually rich documents has a representation problem: important content often lives in tables, charts, figures, and layout relations th

Mind the Rift: Cross-Scale Coupling Mismatch for AI-Generated Video Detection

arXiv:2609.00742v1 Announce Type: new Abstract: As AI video generators achieve cinematic realism, reliable detection becomes essential for safeguarding digital trust. We identify cross-scale coupling

MMAI Gym for Science: Training Liquid Foundation Models for Drug Discovery

arXiv:2603.03517v2 Announce Type: replace-cross Abstract: General-purpose large language models (LLMs) that rely on in-context learning do not reliably deliver the scientific understanding and perform

Modelpedia: A Catalog of Model Findings for the Meta-Science of AI

arXiv:2609.01090v1 Announce Type: new Abstract: Scientific knowledge about AI models is produced faster than the community can organize it. Every few months a new foundation model reshapes the field a

Mudskippers use tail thrusting to help crutching to move on mud of various wetness

arXiv:2609.00564v1 Announce Type: cross Abstract: At the water-land interface, amphibious fishes encounter wet flowable substrates made of granular solid-water mixtures, which can stay solid or flow l

MUGEN: Generating Unlearnable Graph Examples for Multiple Learning Tasks

arXiv:2609.00696v1 Announce Type: new Abstract: Graph data across diverse domains can expose valuable relational information to unauthorized representation learning, creating a pressing need for prote

Multi-View Causal Discovery without Non-Gaussianity: Identifiability and Algorithms

arXiv:2502.20115v4 Announce Type: replace Abstract: Causal discovery is a difficult problem that typically relies on strong assumptions on the data-generating model, such as non-Gaussianity. In practi

Model Releases

MultiGait: A Multi-Sensor Multi-Perspective Multi-Session Biometric Inference Benchmark and its Dataset

model-releasesarxiv-cs-cv

arXiv:2609.01036v1 Announce Type: cross Abstract: A lack of suitable datasets has limited the research into the privacy risks of novel smart city sensors, such as thermal cameras, depth cameras, and l

Neuro-Symbolic Geometric Abstraction (NeuSOGA): From Observations to Symbolic Mathematical Representations

arXiv:2609.01408v1 Announce Type: new Abstract: A fundamental challenge in artificial intelligence is the transformation of observations into explicit symbolic representations suitable for abstraction

Neurosymbolics for Data Engineering: Achieving Long Context Token Reduction Without Finetuning

arXiv:2609.00367v1 Announce Type: cross Abstract: Large Language Models are increasingly deployed for sophisticated data engineering tasks such as generating structured queries from natural language,

OCGQuant: Outlier-Companion Grouping for NVFP4 Quantization

arXiv:2609.00066v1 Announce Type: cross Abstract: NVFP4 is an efficient microscaling format for low-bit inference, but activation outliers can still degrade quantization accuracy within NVFP4 blocks.

On Synthesis of Metric Interval Temporal Logics

arXiv:2609.01032v1 Announce Type: cross Abstract: Automated mining of formal specifications is vital for verifying real-time systems. However, existing passive learning approaches remain restricted to

On the Existence of Consistent Adversarial Attacks in High-Dimensional Linear Classification

arXiv:2506.12454v2 Announce Type: replace-cross Abstract: What fundamentally distinguishes an adversarial attack from a misclassification due to limited model expressivity or finite data? In this work

On-the-Fly3R: Towards Robust Online 3D Reconstruction with Feed-Forward 3R Models for Large-Scale UAV Scenarios

arXiv:2609.00923v1 Announce Type: new Abstract: While feed-forward 3D reconstruction (3R) offers efficient end-to-end modeling, its application in large-scale UAV mapping is hindered by the prohibitiv

On the Reliability of Generative Augmentation: A Wasserstein-Based Theoretical and Empirical Study

arXiv:2609.01410v1 Announce Type: cross Abstract: Generative data augmentation is widely used to mitigate class imbalance, yet its theoretical effect on downstream generalization remains poorly unders

One-Layer Transformer Provably Learns Multiclass One-Nearest Neighbor in Context

arXiv:2609.01311v1 Announce Type: new Abstract: We extend recent work establishing an equivalence between one-layer transformers and nearest-neighbor classifiers in the binary setting to the multiclas

One Print, Many Moves: Monolithic Origami-inspired Folding Actuator for Composable Soft Multi-DoF Systems

arXiv:2609.00751v1 Announce Type: new Abstract: Conventional soft robot actuators excel in compliance, but their uncontrolled deformations compromise accuracy and hinder scaling to multi-degree-of-fre