research

Semantic Triplet Restoration: A Novel Protocol for Hierarchical Table Understanding in Large Language Models

arXiv:2605.31550v1 Announce Type: new Abstract: Table question answering requires models to recover semantic relations encoded implicitly by two-dimensional layout, merged cells, and hierarchical head

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Separating Secrets from Placeholders: A Hybrid CNN-CodeBERT Framework for Three-Class Credential Leakage Detection

DGX agent

arXiv:2605.31520v1 Announce Type: cross Abstract: Credential leakage in public source code repositories poses a critical security threat, with over 23.8 million secrets exposed in 2024 alone. Existing

researcharxiv-cs-ai

1 Jun 2026

ShapDBM: Exploring Decision Boundary Maps in Shapley Space

arXiv:2603.22235v2 Announce Type: replace-cross Abstract: Decision Boundary Maps (DBMs) are an effective tool for visualising machine learning classification boundaries. Yet, DBM quality strongly depe

Shared Doubt: Zero-shot Cross-Lingual Confidence Estimation for Language Models

arXiv:2605.31220v1 Announce Type: cross Abstract: Confidence estimation (CE), i.e. quantifying the reliability of a model's prediction, has attracted great interest in the context of large language mo

SHIELD: Secure Hypernetworks for Incremental Expansion Learning Defense

arXiv:2506.08255v4 Announce Type: replace-cross Abstract: Continual learning under adversarial conditions remains an open problem, as existing methods often compromise either robustness, scalability,

Sinkhorn Normalization of Diffusion Kernels

arXiv:2507.06161v2 Announce Type: replace Abstract: Smoothing a signal based on local neighborhoods is a core operation in machine learning and geometry processing. On well-structured domains such as

Skin Lesion Classification Based on ResNet-50 Enhanced With Adaptive Spatial Feature Fusion

arXiv:2510.03876v2 Announce Type: replace Abstract: Skin cancer classification is challenging due to high inter-class similarity, intra-class variability, and artifacts in dermoscopic images. To addre

SLAP: The Semantic Least Action Principle for Variational Video-Language Modeling

arXiv:2605.30750v1 Announce Type: new Abstract: In the era of Large Video-Language Models (LVLMs), the computational necessity of sparse frame sampling creates a fundamental ``temporal gap'', renderin

SLAT: Segment-Level Adaptive Trimming for Efficient CoT Reasoning

arXiv:2605.30832v1 Announce Type: new Abstract: Recent advances in Large Reasoning Models have significantly improved chain-of-thought (CoT) capabilities via reinforcement learning (RL). However, gene

SlotMemory: Object-Centric KV Memory for Streaming Long-Video Generation

arXiv:2605.31033v1 Announce Type: new Abstract: Streaming video generation models typically rely on temporal-centric memory, which organizes historical context as raw frames, chunk segments, or unclus

SMART: SMPLest-X Mesh Adaptation and RAFT Tracking for Soccer Pose Estimation

arXiv:2605.31551v1 Announce Type: new Abstract: We present our approach to the FIFA Skeletal Tracking Challenge 2026, which requires estimating 3D world-space poses of soccer players from broadcast vi

SPECTRA: Synthetic IR Test Collections with Relevance Oracles and Controlled Distractor Diagnostics

arXiv:2605.31575v1 Announce Type: cross Abstract: Scalable information retrieval testing needs corpora that are large enough to stress index construction, ranking latency, query routing, and evaluatio

Spectral Anatomy of Quantum Gaussian Process Kernels

arXiv:2605.30952v1 Announce Type: new Abstract: Two recent results have reshaped quantum Gaussian processes (QGPs). On the one hand, itet{lowe2025assessing} rule out the exponential speedups claimed b

Speculative Decoding Across Languages

arXiv:2605.30580v1 Announce Type: new Abstract: Speculative decoding has become a crucial component of large language model (LLM) inference, enabling faster generation by drafting multiple tokens and

Speculative Pipeline Decoding: Higher-Accruacy and Zero-Bubble Speculation via Pipeline Parallelism

arXiv:2605.30852v1 Announce Type: new Abstract: Speculative Decoding (SD) accelerates low-concurrency LLM inference by employing a draft-then-verify paradigm. However, mainstream methods typically rel

SteerFace: Debiasing Synthetic Face Generation via Adaptive Residue Perturbation

arXiv:2605.30894v1 Announce Type: new Abstract: The shortage of legally compliant data for face recognition training has sparked growing interest in using synthetic data as an alternative. While recen

Stochastic Gradients under Nuisances

arXiv:2508.20326v2 Announce Type: replace-cross Abstract: Stochastic gradient optimization is the dominant learning paradigm for a variety of scenarios, from classical supervised learning to modern se

Stop the Flip-Flop: Context-Preserving Verification for Fast Revocable Diffusion Decoding

arXiv:2602.06161v2 Announce Type: replace-cross Abstract: Parallel diffusion decoding can accelerate diffusion language model inference by unmasking multiple tokens per step, but aggressive parallelis

Student Capacity Moderates Knowledge Distillation Effectiveness: A Systematic Study Across ResNet Teacher-Student Pairs on CIFAR-10

arXiv:2605.31191v1 Announce Type: cross Abstract: We investigate how teacher-student capacity relationships modulate knowledge distillation (KD) effectiveness in ResNet-based image classification on C

Target-Side Paraphrase Augmentation for Sign Language Translation with Large Language Models

arXiv:2605.31393v1 Announce Type: cross Abstract: Sign language translation (SLT) remains constrained by limited paired sign-video/text corpora and heavy-tailed target vocabularies. We study target-si

TASER: Task-Aware Stein Regularisation for Geometry-Driven Robustness

arXiv:2605.30601v1 Announce Type: new Abstract: Modern deep networks remain fragile under distribution shift and adversarial perturbations, often due to excessive or poorly structured input sensitivit

Technical note on Sequential Test-Time Adaptation via Martingale-Driven Fisher Prompting

arXiv:2510.03839v2 Announce Type: replace Abstract: We present a theoretical framework for M-FISHER, a method for sequential distribution shift detection and stable adaptation in streaming data. For d

The Download: China’s brain implant ambitions

This is today’s edition of The Download, our weekday newsletter that provides a daily dose of what’s going on in the world of technology. China has approved the world’s first invasive brain-computer c

researchmit-tech-review

The Fast Mixing Mechanism for Differential Privacy

arXiv:2605.30600v1 Announce Type: new Abstract: Randomized sketching is a central tool for compressing large-scale optimization problems while preserving accuracy. In particular, sketches that are bas

The Gaussian-Head OFL Family: One-Shot Federated Learning from Client Global Statistics

arXiv:2602.01186v2 Announce Type: replace-cross Abstract: Classical Federated Learning relies on a multi-round iterative process of model exchange and aggregation between server and clients, with high

The Inclusion Depth of Pattern Languages: An Open Problem in Algorithmic Learning Theory

arXiv:2605.30389v1 Announce Type: cross Abstract: Pattern languages are a classical model in formal language theory and algorithmic learning theory. This note formulates the problem of computing the i

The Information Geometry of Softmax: Probing and Steering

arXiv:2602.15293v2 Announce Type: replace-cross Abstract: This paper concerns the question of how AI systems encode semantic structure into the geometric structure of their representation spaces. The

The Latin Substrate: How Language Models Represent and Mediate Script Choice

arXiv:2605.31363v1 Announce Type: new Abstract: Many languages are written in multiple scripts, requiring large language models (LLMs) to generate equivalent linguistic content in distinct orthographi

The SuperActivator Mechanism: Transformers Concentrate Reliable Concept Signals in the Tail

arXiv:2512.05038v2 Announce Type: replace Abstract: Concept vectors aim to enhance model interpretability by linking internal representations with human-understandable semantics, but their practical u

TIC-VLA: A Think-in-Control Vision-Language-Action Model for Robot Navigation in Dynamic Environments

arXiv:2602.02459v2 Announce Type: replace Abstract: Robots in dynamic, human-centric environments must follow language instructions while maintaining real-time reactive control. Vision-language-action

researcharxiv-cs-ro

To Grok Grokking: Provable Grokking in Ridge Regression

arXiv:2601.19791v3 Announce Type: replace Abstract: We study grokking, the onset of generalization long after overfitting, in a classical ridge regression setting. We prove end-to-end grokking results

TokTalk: Expressive Real-time Facial Animation from Audio-LLM Tokens

arXiv:2605.31294v1 Announce Type: new Abstract: Recent advances in Audio-LLMs like GPT-4o have ushered in an era of conversational interaction with language models. Conversational avatars however, sti

Towards Atoms of Large Language Models

arXiv:2509.20784v3 Announce Type: replace-cross Abstract: The fundamental representational units (FRUs) of large language models (LLMs) remain undefined, limiting further understanding of their underl

Towards Efficient LLMs Annealing with Principled Sample Selection

arXiv:2605.31175v1 Announce Type: new Abstract: The annealing phase is a pivotal convergence stage in LLM pre-training that ultimately determines final model quality. However, effectively selecting tr

Toxic HallucinAItions: Perturbing Prompts and Tracing LLM Circuits

arXiv:2605.30913v1 Announce Type: cross Abstract: Large language models (LLMs) are increasingly deployed in conversational settings where user tone ranges from polite to adversarial or toxic, yet less

Trajectory Planning for Non-Communicating Mobile Robots using Inverse Optimal Control

arXiv:2605.30906v1 Announce Type: new Abstract: To enable an efficient interaction of non-communicating mobile robots in collision avoidance scenarios, we present a novel combined trajectory planning

researcharxiv-cs-ro

TransLPRNet: Lite Vision-Language Network for Single/Dual-line Chinese License Plate Recognition

arXiv:2507.17335v2 Announce Type: replace-cross Abstract: License plate recognition in open environments is widely applicable across various domains; however, the diversity of license plate types and

Triangle Splatting SLAM

arXiv:2605.31419v1 Announce Type: new Abstract: We present a dense RGB-D SLAM system using differentiable triangles as the 3D map representation. While 3D Gaussian Splatting has emerged as the leading

TRINE: A Token-Aware, Runtime-Adaptive FPGA Inference Engine for Multimodal AI

arXiv:2603.22867v1 Announce Type: cross Abstract: Multimodal stacks that mix ViTs, CNNs, GNNs, and transformer NLP strain embedded platforms because their compute/memory patterns diverge and hard real

True Self-Avoiding Walk for Accelerating Markov-Chain Monte Carlo Integration

arXiv:2605.30532v1 Announce Type: cross Abstract: We study true self-avoiding walk (TSAW) as a mechanism for improving empirical integral estimation via Markov chain Monte Carlo (MCMC). We consider fi

Trump claims to have mastered the “Art of the Deal,” but he has just given us a master class in negotiating incompetence. I explain why the …

Trump claims to have mastered the “Art of the Deal,” but he has just given us a master class in negotiating incompetence. I explain why the Iranians have the upper hand after his disastrous war of cho

researchyann-lecun--x

TTE-CAM: Self-Explainable Class Activation Maps for Pretrained Black-Box CNNs

arXiv:2603.26885v2 Announce Type: replace Abstract: Convolutional neural networks (CNNs) achieve state-of-the-art performance in medical image analysis yet remain opaque, limiting adoption in high-sta

Two Degree-of-Freedom Vibratory Transport in a Grasp

arXiv:2605.30780v1 Announce Type: new Abstract: In this paper, we use asymmetric vibrations to demonstrate two degree-of-freedom (DoF) in-hand manipulation of grasped parts. The asymmetric vibrations

researcharxiv-cs-ro

Unicorn: Scaling High-Dimensional Time Series Forecasting via Universal Correlation Modeling

arXiv:2605.30376v1 Announce Type: cross Abstract: Modern time series architectures face a fundamental trade-off: channel-independent models scale well with increasing data volume but ignore critical i

Unifying and Optimizing Data Values for Selection via Sequential Decision-Making

arXiv:2502.04554v2 Announce Type: replace Abstract: Data selection has emerged as a crucial downstream application of data valuation, yet the theoretical foundations for using data values in selection

UniMedVL: Unifying Medical Multimodal Understanding and Generation through Observation-Knowledge-Analysis

arXiv:2510.15710v3 Announce Type: replace Abstract: Medical workflows routinely combine reading images with producing visual and textual outputs, making both image understanding and generation central

Universal Decision Learners

arXiv:2605.30694v1 Announce Type: new Abstract: Many theories of decision making -- planning, reinforcement learning, causal intervention, online learning, and game-theoretic equilibrium -- turn local

Universal Multiclass Transductive Online Learning

arXiv:2605.30479v1 Announce Type: new Abstract: We consider the problem of universal transductive online classification with a possibly unbounded label space. This setting considers online learning, w