research

Sample Complexity of Scientific Discovery: PAC Learnability of Compositional Function Trees

arXiv:2606.29331v1 Announce Type: new Abstract: Scientific discovery via symbolic regression is often viewed as statistically and computationally intractable because the hypothesis space of expression

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Sample-Efficient Learning of Probabilistic Causes for Reachability in Markov Decision Processes with Probabilistic Guarantees

DGX agent

arXiv:2606.29681v1 Announce Type: new Abstract: Probabilistic model checking for Markov decision processes (MDPs) provides quantitative guarantees, but often offers limited insight into why undesired

researcharxiv-cs-ai

30 Jun 2026

SAT-RTS: A systematic framework for tactical knowledge extraction and visualization-based analysis in real-time strategy games

arXiv:2606.30090v1 Announce Type: new Abstract: Efficient tactical knowledge extraction and analysis in real-time strategy (RTS) games micromanagement are constrained by the high-dimensional coupled s

Scalable Synthesis of distributed LLM workloads through Symbolic Tensor Graphs

arXiv:2511.10480v3 Announce Type: replace-cross Abstract: Optimizing the performance of large language models (LLMs) on large-scale AI training and inference systems requires a scalable and expressive

ScaleAware-JEPA: Latent Representation for Discovery in Multiscale Physical Fields

arXiv:2606.29723v1 Announce Type: cross Abstract: Continuous physical fields represent a large fraction of data under scientific investigation. Their multiscale structures are central to discovery, ye

SDGIC: A Semantic Disambiguation-Guided Generative Image Compression Method for Ultra-Low Bitrates

arXiv:2512.06344v2 Announce Type: replace Abstract: Generative image compression has recently shown impressive perceptual quality, but often suffers from semantic inconsistency at ultra-low bitrates (

Seed-to-Seed: Unpaired Image Translation in Diffusion Seed Space

arXiv:2409.00654v2 Announce Type: replace Abstract: We introduce Seed-to-Seed Translation (StS), a novel approach that combines GANs and diffusion models (DMs) for unpaired Image-to-Image Translation.

Self-supervised Geometry Reasoning for LiDAR Simultaneous Localization and Mapping

arXiv:2606.30166v1 Announce Type: new Abstract: LiDAR simultaneous localization and mapping (SLAM) relies on local geometric quantities such as covariances, correspondences, and surface structures. Ho

researcharxiv-cs-ro

Semantic-Aware Generative Image Transmission for Resource-Constrained Visual IoT Systems

arXiv:2606.28398v1 Announce Type: new Abstract: Resource-constrained visual Internet of Things (IoT) systems, such as edge cameras, unmanned sensing platforms, industrial inspection nodes, and remote

Semantic Correspondence: Unified Benchmarking and a Strong Baseline

arXiv:2505.18060v4 Announce Type: replace Abstract: Establishing semantic correspondence is a challenging task in computer vision, aiming to match keypoints with the same semantic information across d

SemConFlow: Semantic Grounding of Holistic Co-Speech Gesture Generation with Contrastive Flow-Matching

arXiv:2603.26553v2 Announce Type: replace Abstract: While the field of co-speech gesture generation has seen significant advances, producing holistic, semantically grounded gestures remains a challeng

SemFlowRAG: Directed Semantic Flow from Abstraction to Evidence for Complex Reasoning

arXiv:2606.28447v1 Announce Type: cross Abstract: Retrieval-Augmented Generation (RAG) enhanced by Knowledge Graphs has shown promise in complex multi-hop reasoning tasks. However, existing graph-base

Semi-Supervised Sound Event Detection with Conditional Mixup and Embedding-Level Contrastive Loss

arXiv:2606.29901v1 Announce Type: cross Abstract: Sound event detection (SED) is a core module for acoustic environmental analysis, yet its performance is often limited by scarce labeled data. Recent

Set-Inclusive Uncertainty Modeling for Robust Brain Tumor Segmentation

arXiv:2606.30374v1 Announce Type: cross Abstract: Multimodal MRI is essential for accurate brain tumor segmentation. However, acquiring all modalities at inference is often challenging in practice, wh

Shoot from the HIP: Hessian Interatomic Potentials without derivatives

arXiv:2509.21624v3 Announce Type: replace Abstract: Fundamental tasks in computational chemistry, from transition state search to vibrational analysis, rely on molecular Hessians, which are the second

Sifei at SemEval-2026 Task 8: Hybrid Retrieval and Query Rewriting for Multi-Turn RAG

arXiv:2606.28352v1 Announce Type: cross Abstract: Multi-turn retrieval-augmented generation (RAG) is challenging due to evolving user intent, conversational noise, and strict context limits. We propos

SIGNET: Motion-Level Knowledge Transfer for Cross-Language Sign Language Translation

arXiv:2606.28626v1 Announce Type: new Abstract: Sign language translation (SLT) remains challenging due to its high spatio-temporal complexity, long sequences, and the need to model multiple articulat

Situation Perception: A Necessary Primitive to Artificial Superintelligence

arXiv:2606.30481v1 Announce Type: cross Abstract: Current large language models are extraordinary statistical engines. They compress vast amounts of text into useful patterns and can explain science,

SK-Adapter: Skeleton-Based Structural Control for Native 3D Generation

arXiv:2603.14152v2 Announce Type: replace Abstract: Native 3D generative models have achieved remarkable fidelity and speed, yet they suffer from a critical limitation: inability to prescribe precise

Skin-R1: Clinical Knowledge-Guided Dermatological Diagnosis Using Vision-Language Models

arXiv:2511.14900v2 Announce Type: replace-cross Abstract: Vision--language models (VLMs) have recently shown promise for assisting clinical reasoning in dermatological diagnosis. However, their trustw

SoccerNet 2026 Player-Centric Ball Action Spotting: Per-Player Attention with Agreement-Based Ensembling

arXiv:2606.28389v1 Announce Type: new Abstract: We present our submission to the SoccerNet 2026 Player-Centric Ball Action Spotting challenge, which uses a two-stage pipeline: a Track-Aware Action Det

Solver-Integrated Adversarial Attacking and Training of Neural Operators

arXiv:2510.18989v2 Announce Type: replace Abstract: Neural operators are commonly utilized as fast surrogates for numerical solvers in PDE problems, mapping input functions to solution functions. Howe

SPARKLING: Balancing Signal Preservation and Symmetry Breaking for Width-Progressive Learning

arXiv:2602.02472v2 Announce Type: replace-cross Abstract: Progressive Learning (PL) reduces pre-training computational overhead by gradually increasing model scale. While prior work has extensively ex

SparsePixels: Efficient Convolution for Sparse Data on FPGAs

arXiv:2512.06208v3 Announce Type: replace-cross Abstract: Inference of standard convolutional neural networks (CNNs) on FPGAs often incurs high latency and a long initiation interval due to the deep n

Speculative Pre-Positioning: Decoding Stateful Sessions to the Next Decision Point Off the Critical Path

arXiv:2606.29565v1 Announce Type: new Abstract: A stateless inference server (vLLM, SGLang, TensorRT-LLM) idles between requests while the accelerator waits; a stateful session reclaims that idle time

SSDD: Single-Step Diffusion Decoder for Efficient Image Tokenization

arXiv:2510.04961v2 Announce Type: replace Abstract: Tokenizers are a key component of state-of-the-art generative image models, extracting the most important features from the signal while reducing da

Stability Boundaries and Motor Performance in Delayed Robot-Mediated Dyadic Interactions

arXiv:2510.14511v3 Announce Type: replace Abstract: This paper establishes analytical stability boundaries for robot-mediated human-human (dyadic) interaction systems, subject to haptic communication

researcharxiv-cs-ro

Stabilizing Extrapolation in Looped Transformers via Learned Stochastic Stopping

arXiv:2606.29983v1 Announce Type: cross Abstract: Looped Transformers, which repeatedly apply a shared transformer block, are an architecturally natural fit for variable-length algorithmic tasks. Alth

Steerable Visual Representations

arXiv:2604.02327v2 Announce Type: replace-cross Abstract: Pretrained Vision Transformers (ViTs) such as DINOv2 and MAE provide generic image features that can be applied to a variety of downstream tas

StereoGS: Sparse-View 3D Gaussian Splatting via Stereo Priors

arXiv:2606.30545v1 Announce Type: new Abstract: 3D Gaussian Splatting (3DGS) has achieved remarkable success in real-time novel view synthesis, yet it suffers from severe overfitting under sparse-view

Stimulus Motion Perception Studies Imply Specific Neural Computations in Human Visual Stabilization

arXiv:2506.13506v3 Announce Type: replace Abstract: Even during fixation the human eye is constantly in low amplitude motion, jittering over small angles in random directions at up to 100Hz. This moti

Stochastic Optimal Control Sampling for Diffusion Inverse Problems

arXiv:2606.28785v1 Announce Type: new Abstract: Benefiting from the strong ability to capture data distributions, diffusion models have become powerful tools for solving image inverse problems. The ke

Structural Certification for Reliable Physical Design with Language Models

arXiv:2606.30107v1 Announce Type: new Abstract: An unreliable language model can be made to produce reliable physical designs if the authority to assert is moved out of the model: the model proposes,

Structured Proper Loss Geometries for Multiclass Classification: Theory and Controlled Empirical Evaluation

arXiv:2606.29471v1 Announce Type: new Abstract: Strictly proper scoring rules identify the true conditional class distribution at population level, but their curvature can alter optimization and finit

Supporting Workflow Reproducibility by Linking Bioinformatics Tools across Papers and Executable Code

arXiv:2603.08195v2 Announce Type: replace Abstract: Motivation: The rapid growth of biological data has intensified the need for transparent, reproducible, and well-documented computational workflows.

t-STEP: An interpretable model for Total Electron Content predictions and irregularities estimations

arXiv:2606.29644v1 Announce Type: new Abstract: Earth system infrastructures relying on satellite-based technologies, such as Global Positioning System (GPS) communications, are affected by ionospheri

TACO: A Test and Check Framework for Robust Pose Graph Optimization

arXiv:2606.29851v1 Announce Type: new Abstract: Pose Graph Optimization (PGO) is one of the most widely adopted approaches for solving Simultaneous Localization and Mapping (SLAM) problems. However, P

researcharxiv-cs-ro

Tactile Gesture Recognition with Built-in Joint Sensors for Industrial Robots

arXiv:2508.12435v2 Announce Type: replace-cross Abstract: While gesture recognition using vision or robot skins is an active research area in Human-Robot Collaboration (HRC), this paper explores deep

Text-Conditioned Background Generation for Editable Multi-Layer Documents

arXiv:2512.17151v2 Announce Type: replace Abstract: We present a framework for document-centric background generation with multi-page editing and thematic continuity. To ensure text regions remain rea

The Calibrated Deepfake Trust Score (CDTS): Competence-Coupled Trust Degradation Across Deepfake Detectors

arXiv:2606.29484v1 Announce Type: cross Abstract: Modern deepfake detectors are rarely consumed as bare classifiers. In moderation, provenance, and verification pipelines their output probability is r

The discussion about @elonmusk's comments on humanitarian aid has mostly focused on our values, which seems right. But note that USAID serve…

The discussion about @elonmusk's comments on humanitarian aid has mostly focused on our values, which seems right. But note that USAID served our interests as well as our values, by protecting us from

researchyann-lecun--x

The Effect of Scripts and Formats on LLM Numeracy

arXiv:2601.15251v2 Announce Type: replace Abstract: Large language models (LLMs) have achieved impressive proficiency in basic arithmetic, rivaling human-level performance on standard numerical tasks.

The Forgetting-Retention Dilemma: Certified Unlearning Theory in Continual Learning

arXiv:2606.29832v1 Announce Type: new Abstract: Machine unlearning aims to eliminate the influence of specific data from trained models to safeguard privacy. However, this presents a significant chall

The Fundamental Limits of Valid Transport Map Estimation

arXiv:2606.30574v1 Announce Type: new Abstract: Many modern generative modeling methods, including diffusion models, normalizing flows, and flow matching, estimate transport maps or plans between dist

The Many-Body Problem of the Data Centre

arXiv:2606.30206v1 Announce Type: new Abstract: Modern Artificial Intelligence is often framed as limited by its own disembodiment, as if giving it a body would unlock its true potential. We argue to

The Platonic Defense: Backdoor Defense for Self-Supervised Encoders in the Era of Large Scale Pre-training

arXiv:2606.29451v1 Announce Type: new Abstract: Self-supervised learning (SSL) pretrained models have become a dominant paradigm for visual representation learning, but they are vulnerable to backdoor

The Speedup Paradox: Rethinking Inference Speed-Quality Trade-off in Embodied Tasks

arXiv:2606.28529v1 Announce Type: cross Abstract: Embodied foundation models have recently been widely used to improve robot generalization and task success rates. Previous works apply lossy efficient

The Surprising Effectiveness of Video Diffusion Models for Hand Motion Reconstruction

arXiv:2606.30308v1 Announce Type: new Abstract: 4D hand motion reconstruction from egocentric video is bottlenecked by clear limitations of existing methods: image-based pipelines depend on a detector