Search: “research”

Revisiting Anthropomorphic Reflection Markers in Large Language Model Reasoning

arXiv:2605.28305v1 Announce Type: cross Abstract: Large Language Models (LLMs) often produce explicit reflective traces during complex reasoning, accompanied by anthropomorphic markers such as wait, h

All Blog X Post Paper YouTube Reddit GitHub

Clear filters

Research

Revisiting Graph Autoencoders as Implicit Contrastive Learners

DGX agent

arXiv:2410.10241v2 Announce Type: replace-cross Abstract: Graph autoencoders (GAEs) and graph contrastive learning (GCL) are two major paradigms for self-supervised representation learning on graphs,

researcharxiv-cs-ai

28 May 2026

Robo-Blocks: Generative Scaffolding in End-User Design and Programming of Social Robots

arXiv:2605.28154v1 Announce Type: cross Abstract: Programming social robots is challenging for novice robot programmers due to required expertise in planning, interaction design, and programming. Whil

researcharxiv-cs-ro

S-Cheetah: A Novel Quadrupedal Robot with a 3-DOF Active Spine Learning Agile Locomotion

arXiv:2605.27909v1 Announce Type: new Abstract: The biological spine of quadrupeds enables sagittal flexion/extension, lateral bending, and axial rotation, playing a crucial role in highly agile and d

researcharxiv-cs-ro

Semantic-Aware Interpretable Multimodal Music Auto-Tagging

arXiv:2505.17233v3 Announce Type: replace Abstract: Music auto-tagging is essential for organizing and discovering music in extensive digital libraries. While foundation models achieve exceptional per

SmartDirector: Keyframe-Conditioned Cinematic Video Generation with Narrative Pacing Control

arXiv:2605.27891v1 Announce Type: cross Abstract: The narrative quality of a video fundamentally determines its perceptual value. Although existing video generation methods can produce visually appeal

Stop Suppressing the Tail: Causal Inference for Extreme Events

arXiv:2605.27474v1 Announce Type: cross Abstract: Estimating how an outcome responds to a continuous treatment (the Average Dose-Response Function, or ADRF) is a core causal-inference primitive. Howev

The Decision to Verify: How Warmth and User Characteristics Shape Reliance on Conversational Agents for Information Search

arXiv:2605.28498v1 Announce Type: cross Abstract: Conversational artificial intelligence (AI) provides an efficient and convenient gateway to information access. However, it can cause overreliance whe

Thinned Mean Field Langevin Dynamics

arXiv:2605.28589v1 Announce Type: new Abstract: Several important learning tasks can be formulated as minimizing an entropy-regularized objective over an appropriate space of probability distributions

Tree of Thoughts as a Classical Heuristic Search Problem: Formal Foundations and Design Patterns

arXiv:2605.28566v1 Announce Type: new Abstract: Large Language Models (LLMs) have demonstrated remarkable reasoning capabilities, yet their standard generation process -- auto-regressive token predict

When Discourse Pressures Conflict: Information Structure in Vision-Language Model Outputs

arXiv:2605.28346v1 Announce Type: new Abstract: Vision-language models (VLMs) are increasingly evaluated for whether they identify the right visual content, but little is known about whether they expr

researcharxiv-cs-cl

When prompt perturbations break your A/B test: A valid statistical test for generative surveying

arXiv:2605.27463v1 Announce Type: cross Abstract: Generative surveying -- where collections of LLM-based personas provide feedback on messages -- has emerged as a cheap and scalable alternative to tra

Can LLMs Introspect? A Reality Check

arXiv:2605.26242v1 Announce Type: new Abstract: Can large language models detect and report their own internal states? A number of studies have argued that the answer to this question is yes. We argue

GUI-Libra: Training Native GUI Agents to Reason and Act with Action-aware Supervision and Partially Verifiable RL

arXiv:2602.22190v2 Announce Type: replace-cross Abstract: Open-source native GUI agents still lag behind closed-source systems on long-horizon navigation tasks. This gap stems from two limitations: a

Lost in Sampling: Assessing Lexical Reachability in LLMs via the Word Coverage Score (WCS)

arXiv:2605.27268v1 Announce Type: cross Abstract: Modern Large Language Models (LLMs) are often criticized for producing repetitive and homogeneous text, despite possessing vast latent vocabularies. W

Many Logics, One Methodology: A Plea for Logical Pluralism in Formalised Reasoning (preprint)

arXiv:2605.27246v1 Announce Type: cross Abstract: This position statement looks back on two decades of work on shallow embeddings of non-classical logics in classical higher-order logic (HOL), a line

NSF-SciFy: Mining the NSF Awards Database for Scientific Claims

arXiv:2503.08600v3 Announce Type: replace Abstract: We introduce NSF-SciFy, a comprehensive dataset of scientific claims and investigation proposals extracted from National Science Foundation award ab

researcharxiv-cs-cl

Parsimonious Learning-Augmented Online Metric Matching

arXiv:2605.26886v1 Announce Type: cross Abstract: Learning-augmented algorithms have received significant attention in recent years, particularly in the context of online optimization. Motivated by th

Pusa V1.0: Unlocking Temporal Control in Pretrained Video Diffusion Models via Vectorized Timestep Adaptation

arXiv:2507.16116v2 Announce Type: replace Abstract: The rapid advancement of video diffusion models has been hindered by fundamental limitations in temporal modeling, particularly the rigid synchroniz

researcharxiv-cs-cv

Recon: Reconstruction-Guided Reasoning Synthesis for User Modeling

arXiv:2605.26969v1 Announce Type: cross Abstract: User modeling aims to use language models (LMs) to mimic an individual's behavior from a corpus of past context-action pairs (e.g., conversation turns

RoMo: A Large-Scale, Richly Organized Dataset and Semantic Taxonomy for Human Motion Generation

arXiv:2605.26241v1 Announce Type: new Abstract: Success in generative modeling across language, image, and video demonstrates that large, well-curated datasets are the key driver for building capable

researcharxiv-cs-cv

Tournament-GRPO: Group-Wise Tournament Rewards for Reinforcement Learning in Open-Ended Long-Form Generation

arXiv:2605.26958v1 Announce Type: cross Abstract: Reinforcement learning in open-ended long-form generation is challenging because reliable reference answers and automatic metrics are often unavailabl

Two Speeds of Learning: A Representation-Readout Decomposition of Grokking and Double Descent

arXiv:2605.27078v1 Announce Type: cross Abstract: Training loss and accuracy are the standard signals used to monitor generalization during deep neural network training. Two well-documented phenomena

Understanding the Challenges in Iterative Generative Optimization with LLMs

arXiv:2603.23994v2 Announce Type: replace-cross Abstract: Generative optimization uses large language models (LLMs) to iteratively improve artifacts (such as code, workflows or prompts) using executio

ATWL: A Formal Language for Representing, Comparing, and Reusing Visual Analytics Workflows

arXiv:2605.25489v1 Announce Type: new Abstract: Visual analytics (VA) workflows are inherently complex, involving data transformation, feature engineering, visual representation, and human interpretat

BackWeak: Backdooring Knowledge Distillation Simply with Weak Triggers and Fine-tuning

arXiv:2511.12046v2 Announce Type: replace-cross Abstract: Knowledge Distillation (KD) is essential for compressing large models, yet relying on pre-trained 'teacher' models downloaded from third-party

Different Statistical Perspectives for Understanding Generalisation in Graph Neural Networks

arXiv:2605.25452v1 Announce Type: cross Abstract: Graph Neural Networks (GNN) are currently the most popular approach for learning and prediction on graph-structured data and are deployed in various f

Filtered Posterior Mean Collections: A Unified Framework for Analytical Models of Diffusion Generalization

arXiv:2605.24192v1 Announce Type: cross Abstract: The neural-network denoising functions which form the backbone of image diffusion models are remarkably consistent in their generalization behaviour a

Fuzzy PyTorch: Rapid Numerical Variability Evaluation for Deep Learning Models

arXiv:2605.25991v1 Announce Type: new Abstract: We introduce Fuzzy PyTorch, a framework for rapid evaluation of numerical variability in deep learning (DL) models. As DL is increasingly applied to div

GEESE: Genotype-aware End-to-End Spatio-temporal Embedding for Behavioral Phenotyping

arXiv:2605.24370v1 Announce Type: new Abstract: Behavioral phenotyping of genetic animal models currently requires labor-intensive manual feature engineering that limits reproducibility and scalabilit

Mimir: Large-scale Multilingual Concept Modeling

arXiv:2605.25263v1 Announce Type: cross Abstract: Current language modeling approaches are built around tokens. Text corpora are split into tokens, and models are trained by performing computations on

Multimodality Stacking with Blockwise missing values and application to the PIONeeR biomarkers study for prediction of resistance to immunotherapy

arXiv:2605.25050v1 Announce Type: cross Abstract: Integrating multimodal datasets in clinical oncology is frequently hindered by high dimensionality and blockwise missingness, where entire data source

Model Releases

RoboManipBaselines: A Unified Framework for Imitation Learning in Robotic Manipulation across Real and Simulation Environments

model-releasesarxiv-cs-ro

arXiv:2509.17057v3 Announce Type: replace Abstract: We present RoboManipBaselines, an open-source software framework for imitation learning research in robotic manipulation. The framework supports the

The Multilingual Curse at the Retrieval Layer: Evidence from Amharic

arXiv:2605.24556v1 Announce Type: cross Abstract: Multilingual retrieval increasingly underpins cross-lingual question answering and retrieval-augmented generation. Strong zero-shot scores on multilin

researcharxiv-cs-cl

When Interpretability Becomes a Liability: Adversarial Attacks on CBM Concept Layers

arXiv:2605.25304v1 Announce Type: new Abstract: Concept Bottleneck Models (CBMs) have emerged as a cornerstone approach for interpretable machine learning, providing human-understandable intermediate

Advanced AI Service Provisioning in O-RAN through LLM Engine Integration

arXiv:2605.23809v1 Announce Type: cross Abstract: The Open Radio Access Network (O-RAN) architecture allows AI to be embedded directly into the RAN through modular xApps and rApps, yet creating these

Enhancing Deep Neural Network Reliability with Refinement and Calibration

arXiv:2605.23249v1 Announce Type: cross Abstract: Although deep neural networks (DNNs) achieve high predictive accuracy, their confidence estimates are often unreliable, potentially compromising user

GazeBehavior Annotation Toolkit (GBAT): AI-powered toolkit for automatic annotation of egocentric eye-tracking and video data of child-caregiver interaction

arXiv:2605.22962v1 Announce Type: new Abstract: Video recordings of child-caregiver interactions enable investigation of attentional dynamics during naturalistic behavior. Such multimodal recording al

researcharxiv-cs-cv

Generative AI and the Reorganization of Labor Demand

arXiv:2605.23159v1 Announce Type: cross Abstract: Generative artificial intelligence (AI) is expected to transform work, but less is known about how firms reorganize labor demand as the technology dif

Suicide Risk Assessment from AI-powered Video Surveillance: An Interpretable Framework for Prevention in Metro Stations

arXiv:2605.22904v1 Announce Type: cross Abstract: Understanding and monitoring human behavior in metro stations play an important role in supporting suicide prevention efforts, where early identificat

Algorithm Design and Stronger Guarantees for the Improving Multi-Armed Bandits Problem

arXiv:2511.10619v2 Announce Type: replace Abstract: The improving multi-armed bandits problem is a formal model for allocating effort under uncertainty, motivated by scenarios such as investing resear

Double descent for least-squares interpolation on contaminated data: A simulation study

arXiv:2605.21494v1 Announce Type: new Abstract: Overparametrized models can exhibit an excellent generalization performance, although they should be prone to overfitting according to classical statist

Gradient Descent as a Perceptron Algorithm: Understanding Dynamics and Implicit Acceleration

arXiv:2512.11587v2 Announce Type: replace Abstract: Even for the gradient descent (GD) method applied to neural network training, understanding its optimization dynamics, including convergence rate, i

Regret-Based (epsilon,elta)-optimal Stopping Criteria for Bayesian Optimization

arXiv:2605.22561v1 Announce Type: new Abstract: Bayesian optimization (BO) is a widely used iterative black-box optimization method that utilizes Gaussian process (GP) surrogate models. In practice, B

SCI-Defense: Defending Manipulation Attacks from Generative Engine Optimization

arXiv:2605.21948v1 Announce Type: new Abstract: LLM-based ranking systems are vulnerable to Generative Engine Optimization (GEO) attacks, where adversaries inject semantic signals into product descrip

SepsisAI Orchestrator: A Containerized and Scalable Platform for Deploying AI Models and Real-Time Monitoring in Early Sepsis Detection

arXiv:2605.22331v1 Announce Type: new Abstract: Despite strong predictive results in the clinical machine learning literature, the translation of these models into bedside use remains limited by syste

SWE-MiniSandbox: Container-Free Reinforcement Learning for Building Software Engineering Agents

arXiv:2602.11210v4 Announce Type: replace-cross Abstract: Reinforcement learning (RL) has become a key paradigm for training software engineering (SWE) agents, but existing pipelines typically rely on

Towards Explainability of SLMs by investigating Token Level Activation

arXiv:2605.22377v1 Announce Type: new Abstract: Transformer-based language models such as BERT having 110M+ parameters have revolutionized natural language understanding, yet their internal mechanisms