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Generalized Gaussian Temporal Difference Error for Uncertainty-aware Reinforcement Learning

arXiv:2408.02295v4 Announce Type: replace Abstract: Conventional uncertainty-aware temporal difference (TD) learning often models TD errors as zero-mean Gaussian. This assumption can miss the heavy-ta

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GH-ESD: Grounded Hypothesis-Driven Error Slice Discovery for Instance-Level Vision Tasks

DGX agent

Systematic failures of vision models on semantically coherent subsets, known as error slices, reveal limitations in robustness and evaluation. Existing slice discovery approaches largely model slices

researchapple-ml-research

27 Jul 2026

Hash-QNeRF: Multiresolution Hash Encoding for Quantum Neural Radiance Fields

arXiv:2607.21675v1 Announce Type: cross Abstract: Neural Radiance Fields (NeRF) have revolutionized novel view synthesis, yet their classical implementations remain computationally intensive for high-

Hiding Faces in Plain Sight: Defending DeepFakes by Disrupting Face Detection

arXiv:2412.01101v2 Announce Type: replace Abstract: Face-swapping DeepFakes have become an escalating societal concern, attracting increasing attention in recent years. To counter this, we investigate

Hierarchical Latent Structure Learning through Online Inference

arXiv:2603.19139v2 Announce Type: replace Abstract: Learning systems must balance generalization across experiences with discrimination of task-relevant details. Effective learning therefore requires

HiKV: Hierarchical Importance-Aware KV Cache with Hardware Acceleration for LLM Decoding

arXiv:2607.22389v1 Announce Type: cross Abstract: With the rapid adoption of long-context large language models (LLMs), the continuously growing KV cache during decoding has become the critical memory

InnoText: A Unified Model for Visual Text Generation and Editing

arXiv:2607.22101v1 Announce Type: new Abstract: Diffusion models have recently achieved remarkable success in high-fidelity image synthesis, yet their application to visual text generation and editing

Interior interpretability with attention rollout: contraction and propagation profiles in Transformers

arXiv:2607.22367v1 Announce Type: new Abstract: Feature-attribution methods assign scores relating input variables to a model's output, but do not by themselves characterize how explicitly defined int

Interpretable Depression Detection from Social Media Text Using LLM-Derived Embeddings

arXiv:2506.06616v2 Announce Type: replace Abstract: Accurate and interpretable detection of depressive language in social media can support early identification of mental health conditions and inform

IQ-JEPA: A Joint-Embedding Predictive Architecture with a Hermitian Vision Transformer for Sound Speed and Attenuation Estimation from Ultrasound IQ Data

arXiv:2607.22351v1 Announce Type: new Abstract: The speed of sound in tissue is a prerequisite for well-focused imaging and has diagnostic value, but recovering it from raw pulse-echo channel data is

ISPCloak: Weaponizing ISP for Optimization-Free Physical Camouflage against Deepfake Detectors

arXiv:2607.21897v1 Announce Type: new Abstract: The rapid advancement of generative models has spurred the critical need to evaluate the worst-case robustness of deepfake detectors. In this paper, we

Joint Lossless Compression and Steganography for Medical Images via Large Language Models

arXiv:2508.01782v4 Announce Type: replace-cross Abstract: Recently, large language models (LLMs) have driven promising progress in lossless image compression. However, directly adopting existing parad

Latent Interpolation Learning Using Diffusion Models for Cardiac Volume Reconstruction

arXiv:2508.13826v4 Announce Type: replace-cross Abstract: Cardiac Magnetic Resonance (CMR) imaging is a critical tool for diagnosing and managing cardiovascular disease, yet its utility is often limit

LatentFlow: Visual Analytics for Latent Space Analysis in Molecular Graph Neural Networks

arXiv:2607.21941v1 Announce Type: new Abstract: Chemists and materials scientists increasingly use machine learning models, such as graph neural networks (GNNs), to predict properties of molecules and

Local Synaptic Rules Can Implement a SIGReg Gradient Without Backpropagation

arXiv:2607.21622v1 Announce Type: cross Abstract: We prove that two canonical local synaptic learning rules, the potentiation arm of spike-timing-dependent plasticity (STDP^+) and homeostatic plastici

Longitudinal Random Forests for Sparse and Irregular Response Trajectories

arXiv:2607.21817v1 Announce Type: cross Abstract: Longitudinal studies often collect data at sparse, irregular, and unequally spaced time points. Such heterogeneity is often driven by subject-specific

Low-Altitude Channel Multipath Prediction via Panoramic Perception and Vision-Language Model

arXiv:2607.21953v1 Announce Type: new Abstract: Unmanned aerial vehicle (UAV) communication is expected to support a wide range of low-altitude applications in 6G mobile networks. However, traditional

LunarFM: A Shared Multimodal Representation of the Moon's Surface

arXiv:2607.22408v1 Announce Type: new Abstract: The renewed global focus on lunar exploration, driven by the prospect of in-situ resource utilization and a sustained human presence on the Moon, has cr

Mag4D-SLAM Dataset: A Repeated-Traversal Multi-Modal 4D Geomagnetic Dataset for Localization and Mapping

arXiv:2607.21986v1 Announce Type: new Abstract: Geomagnetic sensing offers an infrastructure-free, absolute orientation reference that is robust to GNSS denial and visual degradation, yet no large-sca

researcharxiv-cs-ro

Measuring the Dependency Gap: Diagnosing Inter-Column Fidelity in Tabular Generative Models

arXiv:2607.21636v1 Announce Type: new Abstract: Synthetic tabular data is valued for preserving not only each column's marginal distribution but the dependencies between columns -- structure that carr

MemNMF: Memory-Augmented NMF on LPC Spectra for Anomalous Sound Detection

arXiv:2607.22086v1 Announce Type: cross Abstract: Autoencoder-based anomalous sound detection is attractive for machine condition monitoring because it can be trained using only normal recordings and

MEUSLI: a Multilingual Projector for LLM-based ASR and Beyond

arXiv:2607.22100v1 Announce Type: new Abstract: Lightweight projectors are an established way to connect pre-trained speech encoders with large language models (LLMs), mapping acoustic features into t

MotifRole-Diff: Risk-Optimal Role-Aware Corruption for Masked Molecular Graph Diffusion

arXiv:2607.21634v1 Announce Type: new Abstract: Masked discrete diffusion for molecular graph generation typically applies a uniform corruption schedule to all tokens in a lossless graph-to-sequence r

Moving Beyond Diversity: Visual Token Pruning as Subspace Reconstruction for Efficient VLMs

arXiv:2606.18681v2 Announce Type: replace Abstract: Despite their remarkable performance, Vision Language Models (VLMs) incur substantial computational overhead due to the large number of visual token

Multi-Horizon Consistency as Geometry: When Latent Dynamics Contract, and When They Do Not

arXiv:2607.21645v1 Announce Type: new Abstract: Multi-horizon latent consistency is a common training knob in video predictors and world models, but practitioners rarely know what it does to transitio

Natural Invariant Measures for Chaotic Game Dynamics: Finding Order in Chaos

arXiv:2607.21805v1 Announce Type: cross Abstract: We study the long-term behavior of the Multiplicative Weights Update (MWU) algorithm in game settings where learning dynamics frequently fail to conve

Numerical Fragility in Transformers: A Layer-wise Theory for Risk Estimation and Selective Stabilization

arXiv:2510.21770v2 Announce Type: replace Abstract: Low-precision execution can induce substantial forward discrepancies in Transformers even for fixed weights and input, yet these discrepancies are u

On Improving Faithfulness of Podcasts from Documents

arXiv:2607.21961v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly used to generate long-form conversational content such as podcasts from textual sources. While these syste

On the Convergence of Stochastic Low-Rank Adaptation

arXiv:2607.21975v1 Announce Type: new Abstract: Low-rank adaptation (LoRA) optimizes J(B,A)=mathcal L(W_base+sBA) over two adapters B in R^{m imes r} and A in R^{r imes n} that form a low-rank update

On the Depth Scalability of Logic Gate Networks

arXiv:2607.21633v1 Announce Type: new Abstract: Logic Gate Networks (LGNs) implement computation through compositions of Boolean operations, yet unlike classical Boolean circuits, existing LGNs do not

Online Pricing and Allocation with Demand Learning and Fulfillment Cost

arXiv:2501.18049v3 Announce Type: replace Abstract: We study online learning for a seller that jointly chooses per-period inventory positions and a uniform price, then fulfills realized demand through

OpenAI called the Hugging Face attack unprecedented. But we’ve been here before.

This story originally appeared in The Algorithm, our weekly newsletter on AI. To get stories like this in your inbox first, sign up here. Reading OpenAI’s account last week of how some of its models b

researchmit-tech-review

Oxygen-TryOn: Fashion-Native Foundation Model for Any-item Virtual Try-On

arXiv:2607.21694v1 Announce Type: new Abstract: We present Oxygen-TryOn, a unified foundation model for any-item virtual try-on. Rather than repurposing a general-purpose image editor, Oxygen-TryOn is

Phylogenetic signal in marine mammal and bird vocalizations captured by audio foundation models: the limited benefit of domain-specific pretraining

arXiv:2607.22458v1 Announce Type: new Abstract: Do learned audio embeddings encode structure that nobody told them to encode? We probe four large pretrained audio models (AST, CLAP, BEATs-bio and Bird

Physiological Signals as a Forensic Modality for Talking-Face Deepfake Detection

arXiv:2607.21776v1 Announce Type: cross Abstract: Talking-face (TF) deepfake generation synthesizes photore- alistic facial video from a static source image and an au- dio signal, producing forgeries

Plug, Play, and Comply: A Modular Framework for Online Variable Impedance with Arbitrarily Oriented Compliance Axes

arXiv:2607.22483v1 Announce Type: new Abstract: The paper proposes a robot-agnostic compliant-control framework that extends the ROS control ecosystem with standardized joint and Cartesian command int

researcharxiv-cs-ro

Predictive Query Language: A Domain-Specific Language for Predictive Modeling on Relational Databases

arXiv:2602.09572v3 Announce Type: replace-cross Abstract: The purpose of predictive modeling on relational data is to predict future or missing values in a relational database, for example, future pur

Prior laundering: learned priors with inherited, undetectable overconfidence

arXiv:2607.21721v1 Announce Type: cross Abstract: Learned generative priors are increasingly used for ill-posed Bayesian inverse problems, their posterior uncertainty treated as earned from data. But

Probing Speaker Identity Sensitivity in Audio Deepfake Detectors

arXiv:2607.21820v1 Announce Type: cross Abstract: Audio deepfake detectors are trained to distinguish genuine speech from synthetic speech and often perform well on standard benchmarks. Yet the same d

Progress Reward Modeling for Robotic Learning: A Comprehensive Survey

arXiv:2607.21655v1 Announce Type: cross Abstract: Robotic learning takes place in dynamic environments with large behavior spaces. A terminal success signal only tells the robot whether the task is co

Re-FORC: Adaptive Reward Prediction for Efficient Chain-of-Thought Reasoning

arXiv:2511.02130v2 Announce Type: replace-cross Abstract: We propose Re-FORC, an adaptive reward prediction method that, given a query, enables prediction of the expected future rewards as a function

Really interesting concept -- instead of optimizing against static benchmarks or internally generated reward models, agents are evaluated th…

researchfrancois-chollet--x

Really interesting concept -- instead of optimizing against static benchmarks or internally generated reward models, agents are evaluated through real economic interactions. Using an external market a

Reasoning Denoiser: Denoising Reasoning Traces for Hallucination Detection in Large Reasoning Models

arXiv:2607.22098v1 Announce Type: cross Abstract: Large reasoning models (LRMs) generate long reasoning traces before producing final answers. While these traces may contain useful signals for halluci

Reflector: Arrangement-Aware Harmonic Retrieval for Sample-Based Composition

arXiv:2607.22413v1 Announce Type: cross Abstract: Sample retrieval tools can help composers find harmonically compatible material, but querying from a fixed reference sample becomes less informative a

Relaxed activation analysis of dataflow networks - A clock calculus for machine learning and real-time scheduling

arXiv:2607.21797v1 Announce Type: cross Abstract: Previous work has shown that the simple dataflow primitives of the Lustre language allow the natural, semantically unambiguous, and compact representa

Remedying Coarsening-Based GNN Training under Heterophily via Adaptive Complementary Enhancement

arXiv:2607.21885v1 Announce Type: new Abstract: Coarsening-based training for graph neural networks (GNNs), i.e. training on coarsened graphs rather than the original large ones, has become a promisin

Rethinking Multi-Branch and Cross-Backbone Fusion for Vehicle Re-Identification in the Foundation-Model Era

arXiv:2607.22068v1 Announce Type: new Abstract: Multi-branch architectures and CNN-Transformer fusion have long been regarded as effective ways to improve vehicle re-identification (Re-ID) by combinin

Robot Learning to Communicate through Projected Visual Abstractions

arXiv:2607.22434v1 Announce Type: new Abstract: Humans routinely communicate through abstractions of their bodies, including shadows, silhouettes, and reflections. Yet robots remain largely confined t

researcharxiv-cs-ro