Search: “research”

The Value of a Prompt: An LLM-Relative Kolmogorov-Complexity Approach

arXiv:2608.16438v1 Announce Type: new Abstract: In a world where valuable artifacts are increasingly created, completed, or processed by LLMs, the central economic question is not only what the LLM ca

Human

Content type

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Thinking Outside the (Gray) Box: A Context-Based Score for Assessing Value and Originality in Neural Text Generation

DGX agent

arXiv:2502.13207v4 Announce Type: replace-cross Abstract: Despite the increasing use of large language models for creative tasks, their outputs often lack diversity. Common solutions, such as sampling

researcharxiv-cs-ai

18 Aug 2026

TIMA: Text-Image Mutual Awareness for Balancing Zero-Shot Adversarial Robustness and Generalization Ability

arXiv:2405.17678v2 Announce Type: replace-cross Abstract: Achieving zero-shot adversarial robustness without sacrificing generalization remains challenging for foundation models such as CLIP, especial

TokenSTFormer: A Tokenized Spatial-temporal Attention Model for Holistic Motion Analysis in Adolescent Idiopathic Scoliosis Screening

arXiv:2608.16122v1 Announce Type: cross Abstract: Adolescent Idiopathic Scoliosis (AIS) is a prevalent spinal deformity in adolescents that, if left untreated, can result in severe health outcomes. Tr

Toward Optimal Second-Order Path-Length Guarantee for Adversarial Multi-Armed Bandits

arXiv:2608.15996v1 Announce Type: new Abstract: We study second-order path-length regret in adversarial K-armed bandits against oblivious loss sequences. Bubeck et al. [2019] designed an algorithm tha

Towards Computational Provenance: Carrying Causal-State Evidence in Generated Text

arXiv:2608.16868v1 Announce Type: cross Abstract: A language model's output does not by itself provide verifiable evidence about the internal computation that produced it. We study computational prove

Agents

Towards Risk-free AI Agent Deployment

arXiv:2608.16411v1 Announce Type: cross Abstract: LLM-based agents are rapidly moving from research prototypes into the core business processes of organizations, but these agents pose deployment risks

agentsarxiv-cs-ai

Applications

Towards Unified Approaches in Self-Supervised Event Stream Modeling: Progress and Prospects

arXiv:2502.04899v3 Announce Type: replace-cross Abstract: The proliferation of digital interactions across diverse domains, such as healthcare, e-commerce, gaming, and finance, has resulted in the gen

applicationsarxiv-cs-ai

Training-Free Long-Term Multi-Object Tracking for Sports Video Analytics

arXiv:2608.15688v1 Announce Type: new Abstract: Long-term multi-object tracking in sports remains challenging due to frequent occlusions, rapid camera motion, and repeated player reappearances. We int

Training-Free Multi-Concept Image Editing

arXiv:2602.20839v3 Announce Type: replace Abstract: Training-free image editing with diffusion models is highly desirable yet is complex and remains a significant challenge. While recent optimisation-

Transfer Learning of Keystroke Dynamics for Cross-Device User Authentication

arXiv:2608.16334v1 Announce Type: new Abstract: Keystroke dynamics (typing patterns) can be used as a behavioural biometric modality for user authentication, with applications such as fraud prevention

TransfHAR: Self-Supervised Wrist Representations for On-Demand Activity Recognition

arXiv:2608.15861v1 Announce Type: new Abstract: Fine-grained wrist activity recognition can support applications such as procedural step guidance and context-aware assistance, yet acquiring labeled da

Translating finite-domain integer constraint models to CP/SMT/ILP/PB/SAT solvers with CPMpy

arXiv:2608.15143v1 Announce Type: new Abstract: Constraint solving is a declarative approach for solving combinatorial satisfaction and optimization problems. The user specifies their problem through

Turning spectra into images improves plant trait retrieval with 2D-CNNs

arXiv:2608.16661v1 Announce Type: new Abstract: Hyperspectral reflectance spectroscopy enables non-destructive estimation of plant functional traits, yet current deep learning approaches process spect

Two by Two: Learning Multi-Task Pairwise Objects Assembly for Generalizable Robot Manipulation

arXiv:2504.06961v2 Announce Type: replace-cross Abstract: 3D assembly tasks, such as furniture assembly and component fitting, play a crucial role in daily life and represent essential capabilities fo

UC-VLM: Consistency-Driven Learning for AI-Generated Image Detection with Vision-Language Large Models

arXiv:2608.15238v1 Announce Type: new Abstract: Vision-Language Large Models (VLLMs) are promising for AI-generated image (AIGI) detection because they can produce both a prediction and a natural-lang

Ultra: Unsupervised Cross-Task Optimization for Reliable Restoration Segmentation Collaboration under Adverse Weather

arXiv:2608.16589v1 Announce Type: new Abstract: Unsupervised Domain Adaptation for Adverse Weather Semantic Segmentation (UDA-ASS) aims to transfer semantic knowledge from labeled normal-weather image

Uncertainty Identifies Difficult Samples Across Methods: A Multi-Task Study on a Heterogeneous Skin Lesion Dataset

arXiv:2608.14768v1 Announce Type: new Abstract: Skin lesion classifiers can be confidently wrong on the cases that matter most, so knowing when a prediction should not be trusted is clinically as usef

Uncovering Hidden Leptonic Correlations with Flow Matching and Autoencoders

arXiv:2608.15042v1 Announce Type: cross Abstract: We perform a global search for values of the Yukawa matrices and Majorana masses in the Type-I seesaw mechanism. Using flow matching, which is a gener

Unified Condition-Action Modeling for Accurate One-Step Action Generation

arXiv:2608.16153v1 Announce Type: new Abstract: Robot manipulation requires policies that are both accurate and efficient, as robot control must respond to changing observations under tight latency co

researcharxiv-cs-ro

Unifying Graph Neural Networks Through a Common Layer Equation

arXiv:2608.16097v1 Announce Type: new Abstract: Graph neural networks are commonly described through family-specific equations whose notation obscures shared computations and structural differences. W

Unlocking Motion in Expressions: Temporal Calibration for Referring Video Object Segmentation

arXiv:2608.16332v1 Announce Type: new Abstract: Referring Video Object Segmentation (RVOS) aims to segment referred objects at the pixel level in video sequences based on natural language descriptions

Unraveling the Size Determination Mechanism of Nanocrystal Synthesis via Interpretable Neural Networks

arXiv:2608.14734v1 Announce Type: cross Abstract: Deep learning models of nanocrystal synthesis enable the prediction of size and shape by encoding precursors and reaction conditions. However, their b

Unsupervised Learning of Cell Instances with Generative Routing Pyramids

arXiv:2608.16810v1 Announce Type: new Abstract: Identifying and representing object instances such as cells or nuclei is a common task in microscopy image analysis. Established machine learning workfl

Using the Mimi codec for metalinguistic representations

arXiv:2608.15799v1 Announce Type: new Abstract: In this paper, we focus on the dictionary of 2048 tokens used in Mimi semantic token codebook, the neural codec of the Moshi language model. We show tha

researcharxiv-cs-cl

VesselBridge3D: A Foundation Model Adaptation Framework for Label-Efficient 3D Vessel Segmentation

arXiv:2602.23782v2 Announce Type: replace-cross Abstract: State-of-the-art vessel segmentation methods typically require large-scale annotated datasets and suffer from severe performance degradation u

VicEdit: Learning to Edit Videos from Visual In-Context Examples

arXiv:2608.16745v1 Announce Type: new Abstract: Despite progress in instruction-based video editing, unimodal textual instructions inherently struggle to convey fine-grained textures and complex dynam

VisDom: Sparse Novel View Synthesis with Visible Domain Constraint

arXiv:2606.20531v2 Announce Type: replace Abstract: Sparse novel view synthesis (NVS) remains challenging due to the ambiguity of recovering 3D geometry from few input views. While NeRF- and Gaussian

Model Releases

We still don’t know how people are really using AI

model-releasesmit-tech-review

AI companies like Anthropic and OpenAI regularly publish reports on how people are using products like Claude and ChatGPT, but they only release the data they want us to see, AI researchers say. “Ther

What Makes a Good Layer? Assessing the Layer-Wise Intrinsic Properties of Music Foundation Models

arXiv:2608.14819v1 Announce Type: cross Abstract: Music foundation models are commonly used as frozen audio feature extractors, yet selecting which layer to extract from remains largely heuristic. Cur

What the Reranker Sees: Multi-Aspect Page Annotation for Long-Document Multimodal Question Answering

arXiv:2608.14841v1 Announce Type: new Abstract: Long-document visual question answering (VQA) over documents of tens to hundreds of pages mixing text, tables, charts, and figures typically follows ret

What You Ask is What You Ground: Bridging Question Intent to Temporal Evidence for Grounded VideoQA

arXiv:2608.15708v1 Announce Type: new Abstract: We study a critical yet overlooked failure mode in Grounded Video Question Answering: question-invariant grounding, where models predict nearly identica

When Uncertainty Isn't Enough: An Empirical Study of Self-Correction in Code Generation

arXiv:2608.14659v1 Announce Type: new Abstract: Large language models for code generation often produce incorrect solutions without reliable indicators of failure. We study whether uncertainty estimat

Which Question Is Your Attention Metric Answering? Attention Rows as Compositional Data

arXiv:2608.14712v1 Announce Type: cross Abstract: Each row of a transformer's attention matrix is a probability distribution over tokens, and in trained models most of that probability lands on a sing

Who Leads Now? Token-Level Modality Arbitration for Chart-to-Code Generation

arXiv:2608.15510v1 Announce Type: new Abstract: Chart-to-code generation requires a model to read the fine-grained visual details of a chart and write executable code that reproduces it. Existing char

Wolff-Parkinson-White Detection at 471:1 Class Imbalance: A Leakage-Controlled Study of the Data Bottleneck

arXiv:2608.14633v1 Announce Type: cross Abstract: Wolff-Parkinson-White (WPW) syndrome is a congenital cardiac pre-excitation, clinically important and often missed on the resting 12-lead ECG. Detecti

WorldRover: A Scalable Synthetic Video Data Engine for World Exploration with Rich Annotations

arXiv:2608.15659v1 Announce Type: new Abstract: Learning to generate or reconstruct explorable worlds requires video paired with more than RGB: camera motion, scene geometry, temporal correspondence a

Xemo-Talker: Unlock Emotions Explicitly for Audio-Driven Talking Portrait Synthesis

arXiv:2608.14700v1 Announce Type: new Abstract: Precise emotion control in audio-driven talking heads remains a challenge due to the reliance on implicit emotion regulation in existing systems, which

A Data-Driven Algorithm for Model-Free Control Synthesis

arXiv:2602.13157v2 Announce Type: replace-cross Abstract: Presented is an algorithm to synthesize the optimal infinite-horizon LQR feedback controller for continuous-time systems. The algorithm does n

researcharxiv-cs-ro

A Generalized Parallelogram Rule for Proportional Analogies on Riemannian Manifolds

arXiv:2608.14220v1 Announce Type: new Abstract: Analogies are quaternary relations of the form 'a is to b as c is to d', usually denoted a : b :: c : d. This notion is formalized in particular with th

A Hybrid LLM-Based Framework for Automated Security Annotation Generation in Business Process Models

arXiv:2608.14370v1 Announce Type: cross Abstract: The modelling and analysis of secure business processes require the incorporation of security annotations into process models. Although BPMN extension

A Probabilistic Framework for Learnable Optimization Algorithms

arXiv:2408.11629v2 Announce Type: replace Abstract: We propose a statistical-learning framework for optimization algorithms. The framework is based on probability distributions over optimization traje

A Subjective Study on a New Sharpness Informed Class of Metrics

arXiv:2608.13989v1 Announce Type: cross Abstract: Perceptual loss functions in Deep Neural Network (DNN) deblurring architectures improve the overall quality of restored images. However, few focus on

Model Releases

Act2Intention: A Benchmark For Developing Active Mobile Agents Through Inferring User Intention from GUI Actions

model-releasesarxiv-cs-ai

arXiv:2608.14132v1 Announce Type: cross Abstract: Mobile GUI Agents powered by multimodal large language models (MLLMs) show promise in human-computer intelligence. However, current research primarily

Active Perception for Embodied Disambiguation

arXiv:2608.13605v1 Announce Type: new Abstract: Natural language provides robots with a flexible task interface, but target ambiguity in embodied environments arises not only from user intent; it can

Active Regression via Linear-Sample Sparsification

arXiv:1711.10051v4 Announce Type: replace Abstract: We present an approach that improves the sample complexity for a variety of curve fitting problems, including active learning for linear regression,

Model Releases

AI-Assisted Discovery and Construction of a Counterexample to the Convergence of Three-Block ADMM with the Identity Matrix as its Third Constraint Block

model-releasesarxiv-cs-ai

arXiv:2608.14396v1 Announce Type: cross Abstract: The alternating direction method of multipliers (ADMM), as a landmark algorithm, has attracted tremendous research attention and extensive practical a

APTER: Adaptive Post-Training with Expert-Grounded Rubrics

arXiv:2608.14212v1 Announce Type: new Abstract: As large language models enter professional domains, they must satisfy domain constraints, include critical evidence, and provide complete reasoning rat