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Sparse Autoencoders for Interpretable Emotion Control in Text-to-Speech

arXiv:2606.01479v1 Announce Type: new Abstract: Integrating large language models (LLMs) into text-to-speech (TTS) systems has improved speech expressiveness, yet interpretable emotional control remai

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Spatio-Temporal Reconnection for Multi-Robot Networks using Adaptive Prescribed-Time CBFs

DGX agent

arXiv:2606.01526v1 Announce Type: new Abstract: In multi-robot systems, maintaining persistent communication graph connectivity is often overly restrictive, especially when robots have limited communi

researcharxiv-cs-ro

2 Jun 2026

Speculative Sampling For Faster Molecular Dynamics

arXiv:2606.02455v1 Announce Type: new Abstract: Molecular dynamics (MD) is a key tool for simulating the dynamical behavior of atomic systems. However, MD is inherently serial, which makes it difficul

SpikeReg: Energy-Efficient 3D Deformable Medical Image Registration with Spiking Neural Networks

arXiv:2605.25144v2 Announce Type: replace Abstract: Deformable medical image registration aligns anatomical structures across images but remains computationally dense at 3D resolution. Spiking neural

Splatshot: 3D Face Avatar Generation from a Single Unconstrained Photo

arXiv:2606.01493v1 Announce Type: new Abstract: Reconstructing a photorealistic 3D face avatar from a single unconstrained photograph is challenging: feed-forward 3D Gaussian Splatting (3DGS) models d

STARFISH: faST Accuracy Recovery in pruned networks From Internal State Healing

arXiv:2606.01126v1 Announce Type: cross Abstract: Pruning is a process designed to reduce the number of weights in a large neural network. This can substantially speed up inference but might cause a c

Statistical Analysis of using the Shapley Value for Sensor Anomaly Localization with Accurate Classifiers

arXiv:2606.00867v1 Announce Type: cross Abstract: Recent publications have suggested using the Shap- ley value for sensor anomaly/attack localization. We study the performance of such an approach by u

Statistical Guarantees for Reasoning Probes on Looped Boolean Circuits

arXiv:2602.03970v3 Announce Type: replace-cross Abstract: We study the statistical behavior of reasoning probes in a stylized model of iterative computation inspired by neural algorithmic reasoning. T

Statistical Testing on Directed Graphs by Surrogate Data Generation

arXiv:2606.00758v1 Announce Type: cross Abstract: In recent years, graph signal processing has emerged as a powerful framework at the intersection of signal processing and graph theory, providing tool

Step-Level Sparse Autoencoder for Reasoning Process Interpretation

arXiv:2603.03031v2 Announce Type: replace Abstract: Large Language Models (LLMs) have achieved strong complex reasoning capabilities through Chain-of-Thought (CoT) reasoning. However, their reasoning

Stochastic convergence of parallel asynchronous adaptive first-order methods

arXiv:2606.01787v1 Announce Type: new Abstract: A new class of asynchronous adaptive first-order optimization methods is introduced, comprising asynchronous variants of several popular algorithms. Ver

Stochastic Rounding Increases Small Singular Values

arXiv:2606.00312v1 Announce Type: cross Abstract: Over the past half-dozen years, stochastic rounding (SR) has regained significant attention as a quantization scheme for low-precision floating-point

Structure and Scale in Simplicial Sequence Modelling

arXiv:2606.01302v1 Announce Type: new Abstract: Modern large-scale deep learning exhibits two striking empirical phenomena: behavioural scaling laws (predictable performance gains with increasing scal

Structured Visual Evidence Decomposition for Evidence-Grounded Multimodal Screening of Obstructive Sleep Apnea-Hypopnea Syndrome

arXiv:2606.00087v1 Announce Type: cross Abstract: Effective pre-polysomnography screening for obstructive sleep apnea-hypopnea syndrome (OSAHS) requires combining clinical risk factors with visible cr

Subliminal Learning Is Steering Vector Distillation

arXiv:2606.00995v1 Announce Type: new Abstract: Subliminal learning refers to a student language model acquiring a teacher's traits (e.g. a system-prompted preference for owls) when fine-tuned on the

Symmetric Hermite quadrature-based balanced truncation for learning linear dynamical systems from derivative data

arXiv:2606.00298v1 Announce Type: cross Abstract: Data-driven reduced-order modeling is an essential component in the computer-aided design of control systems. In this work, we present a novel symmetr

Synthesizing Neural Network Controllers with Closed-Loop Dissipativity Guarantees

arXiv:2404.07373v2 Announce Type: replace-cross Abstract: This paper presents a method to synthesize neural network controllers to maximize reward subject to the hard constraint that the feedback syst

Synthetic Data from Cross-Domain Events for Large-Scale Recommendation Systems

arXiv:2606.00282v1 Announce Type: cross Abstract: Large-scale recommendation systems operate across diverse domains, yet they face the challenges of data sparsity and noisy implicit feedback. Traditio

T-CLIP: Enabling Thermal Perception for Contrastive Language-Image Pretraining

arXiv:2606.00673v1 Announce Type: new Abstract: Thermal imaging offers a powerful alternative to visible-spectrum vision under challenging conditions such as low illumination and adverse weather, yet

TabChange: Precise Attribute Changes in Tabular Data

arXiv:2606.00503v1 Announce Type: cross Abstract: Modifying an attribute in tabular data often introduces an unnatural instance by breaking its relationships with other attributes. The modified instan

TalkTag: Fine-Grained Morphosyntactic Error Annotation for Transcribed Speech

arXiv:2606.01820v1 Announce Type: new Abstract: Fine-grained morphosyntactic error annotation is important in clinical and developmental language research, yet it is labour-intensive, expert-dependent

Taming the Loss Landscape of PINNs with Noisy Feynman-Kac Supervision: Operator Preconditioning and Non-Asymptotic Error Bounds

arXiv:2606.00643v1 Announce Type: cross Abstract: Physics-Informed Neural Networks (PINNs) often train slowly or fail to converge on challenging partial differential equations (PDEs), a behavior recen

TAP-JEPA: Frozen Future-Latent Probing and Two-Stage Score Fusion for EPIC-KITCHENS-100 Action Anticipation

arXiv:2606.00662v1 Announce Type: new Abstract: This report presents TAP-JEPA, our runner-up submission to the EPIC-KITCHENS-100 (EK-100) Action Anticipation Challenge at EgoVis 2026. The task is to a

TAPS: Target-Aware Prefix Tree Selection for Diffusion-Drafted Speculative Decoding

arXiv:2606.00487v1 Announce Type: new Abstract: Using a diffusion model for parallel drafting is a promising approach for speculative decoding. By predicting tokens at multiple future positions in a s

Task Structure Reverses Layerwise State Encoding in Sequence Models

arXiv:2606.00926v1 Announce Type: cross Abstract: Mechanistic studies of sequence models often treat layerwise state encodings as architectural traits: recurrent models concentrate readable state, att

Tempora: Characterising the Time-Contingent Utility of Online Test-Time Adaptation

arXiv:2602.06136v2 Announce Type: replace-cross Abstract: Test-time adaptation (TTA) offers a compelling remedy for machine learning (ML) models that degrade under domain shifts, improving generalisat

Temporal Evidence Routing with Structured Visual Evidence for TimeLogicQA

arXiv:2606.01106v1 Announce Type: new Abstract: TimeLogicQA evaluates whether video question answering systems can reason over temporal relations such as event existence, ordering, persistence, bounda

Temporal Motif Signatures for Temporal Graph Neural Networks

arXiv:2606.01176v1 Announce Type: new Abstract: Real temporal interaction streams carry predictive structure in short-horizon motif patterns -- repetition, reciprocity, star diversity, triadic flow --

TERRA: Task-Embedded Reasoning and Representation Architecture for Cross-Domain Applications

arXiv:2606.01520v1 Announce Type: new Abstract: A single action-conditioned latent predictive architecture can in principle be trained on the structured state of a driving scene, a robot workspace, or

Test-Time Training for Zero-Resource Dense Retrieval Reranking

arXiv:2606.01070v1 Announce Type: cross Abstract: Dense retrievers excel at first-stage candidate generation but lack effective reranking in zero-resource settings. Existing approaches face a fundamen

The Download: AI can run your admin department now

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. How small businesses can leverage AI From accounting to design

researchmit-tech-review

The Entropic Signature of Class Speciation in Diffusion Models

arXiv:2602.09651v2 Announce Type: replace-cross Abstract: Diffusion models do not recover semantic structure uniformly over time. Instead, samples transition from semantic ambiguity to class commitmen

The Geometry of Grokking: Norm Minimization on the Zero-Loss Manifold

arXiv:2511.01938v3 Announce Type: replace-cross Abstract: Grokking is a puzzling phenomenon in neural networks where full generalization occurs only after a substantial delay following the complete me

The Lie We Tell: Correcting the Euclidean Fallacy in Vision Language Action Policies via Score Matching on Tangent Space

arXiv:2606.01847v1 Announce Type: cross Abstract: Diffusion-based Vision-Language-Action policies achieve remarkable success in robotic manipulation, yet commit a fundamental geometric error we term t

The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace

arXiv:2606.00182v1 Announce Type: cross Abstract: Human-AI collaboration is considered the most promising way to incorporate AI in the workplace. What remains unexplored are the experiential consequen

The Representation-Rationalizability Tradeoff in Reward Learning

arXiv:2606.00291v1 Announce Type: cross Abstract: In RLHF, each training example contains a prompt x and two candidate responses y,y', and annotators provide pairwise preferences between these respons

The Right Inference Strategy Is All You Need: Nearly Training-Free Domain-Wise Inference for EgoCross Challenge

arXiv:2606.00829v1 Announce Type: new Abstract: EgoCross evaluates multimodal large language models on egocentric video question answering under substantial domain shift, where test videos come from s

The Role of Ambiguity in Error Prediction via Uncertainty Quantification

arXiv:2606.02093v1 Announce Type: cross Abstract: The task of Error Prediction, namely predicting whether a model output is correct, is commonly tackled with Uncertainty Quantification (UQ). However,

Theoretical Analysis of Engression and Reverse Markov Engression

arXiv:2606.01002v1 Announce Type: cross Abstract: Engression is a recently proposed and effective framework for conditional distribution learning. Its multi-step Reverse Markov extension further impro

Thinking Economically: A Hierarchical Framework for Adaptive-Complexity Reasoning in LLMs

arXiv:2606.01168v1 Announce Type: new Abstract: Chain-of-Thought (CoT) has significantly enhanced LLM reasoning, yet often incurs substantial computational overhead due to 'overthinking': generating e

ThinkSwitch: Context Distillation with LoRA and Weight Interpolation for Specific-Purpose Reasoning Tasks

arXiv:2606.01080v1 Announce Type: cross Abstract: Large language models often improve on difficult tasks by spending inference-time compute on a reasoning trace before producing the final answer. That

TimeBlocks: Foundational and Continual Time-Series Blockbase -- Extended Version

arXiv:2606.02142v1 Announce Type: new Abstract: The ongoing digitization has led to a proliferation of time-series data streams that monitor a variety of processes, from which valuable insights may be

TN-SHAP-G: Graph-Structured Tensor Network Surrogates for Shapley Values and Interactions

arXiv:2606.01540v1 Announce Type: cross Abstract: Shapley values are a widely used tool for attributing importance and interactions among input variables in black-box models, but their computation inv

Topological texture analysis of microscopy images of dynamic casein gelation and its relation to rheological properties

arXiv:2606.02048v1 Announce Type: new Abstract: We propose a novel computational toolbox that integrates Topological Data Analysis (TDA), Differential Box Counting (DBC), Multifractal Partition (MFP),

Topology-Aware State Abstraction with Tangle Cores for Markov Decision Processes

arXiv:2606.00427v1 Announce Type: new Abstract: State abstraction in reinforcement learning is usually formulated as a partition of states based on reward and transition similarity. This excludes a co

Towards 3D-Aware Video Diffusion Models: Render-Free Human Motion Control with Mesh Tokenization

arXiv:2606.02000v1 Announce Type: cross Abstract: Diffusion models have shown remarkable success in video generation. However, whether such models are truly aware of the 3D structure underlying visual

Towards Resolving Optimization Conflicts Between Image- and Text-Based Person Re-Identification

arXiv:2606.02242v1 Announce Type: cross Abstract: The joint optimization of image-based (I2I) and text-based (T2I) person re-identification (ReID) is hindered by modality discrepancies and conflicting

Training-Free Composed Video Retrieval via Visual Representation-Guided Video-LLM Reasoning

arXiv:2606.02321v1 Announce Type: new Abstract: Recent advances in large vision-language models have expanded video retrieval from simple text-based search to more flexible scenarios, where users may