All Articles
17317 articles total
path_boost: A Python Package for Interpretable Graph-Level Prediction using Path-Based Gradient Boosting
Presentation of path_boost, a Python package for interpretable graph-level prediction using path-based gradient boosting.
Linear Attention Architectures: Mechanisms, Trade-offs, and Cross-Layer Routing
A comparative study of linear attention architectures (DeltaNet, Gated DeltaNet, etc.) focusing on memory decay, throughput, and cross-layer routing.
Beyond Thermal Imaging: Inferring Thermophysical Properties from Time-Resolved Thermal Observations
Introduction of ThermoField, a framework for inferring thermophysical properties and reconstructing 3D thermal scenes using differentiable heat-transfer simulation.
A Multi-cluster Boundary Learning Method for Out-of-Scope Intent Detection via MiniLM Embedding
A multi-cluster boundary learning method using MiniLM embeddings for more efficient out-of-scope intent detection in human-machine interaction.
When Implausible Tokens Get Reinforced: Tail-Aware Credit Calibration for LLM Reinforcement Learning
Introduction of TACO (Tail-Aware Credit calibratiOn), a method to improve LLM reinforcement learning by preventing the reinforcement of implausible 'tail' tokens.
3100 Opinions on Code Review in an AI World: Building Causal Theory from Practitioner Discourse
A large-scale analysis of practitioner discourse to build a causal theory on how AI coding agents impact the software code review process.
DreamCharacter-1: From 3D Generative Foundation Models to Product-Ready Character Generation
Introduces DreamCharacter-1, a lightweight framework for enhancing 3D foundation models to generate production-ready 3D characters with improved geometry and textures.
From Triggers to Emotions: A CPM-Grounded Appraisal Multi-Agent for Dynamic Emotional Evolution in Persona-Based Dialogue
Proposes CPM-MultiAgent, a framework that uses psychological theory to model dynamic emotional evolution in persona-based dialogue agents.
Shift & Drift: A Zero-Shot Benchmark for Generalizable and Robust Autonomous Driving Motion Planning
Presents Shift & Drift, a zero-shot benchmark to test the robustness and generalization of autonomous driving motion planners against semantic and state-distribution shifts.
Kime-Representation Formulations of Three Open Problems in the Foundations of Classical Mechanics: Uncertainty, Invariant Entropy, and Directional Degrees of Freedom
Provides mathematical formulations in the complex-time (kime) representation to address open problems in classical mechanics regarding uncertainty and entropy.
Multi-agent Autoformalization of Tensor Network Theory
Demonstrates an agent-driven workflow for the autoformalization of theoretical physics in Lean, specifically for tensor network theory, and releases the TNLean library.
Time-to-Collision Based Dynamic Obstacle Avoidance Using Pretrained Vision Models for Robots in Unstructured Environments
Presents a data-efficient method for robotic dynamic obstacle avoidance using pretrained vision models (UniDepth) to compute time-to-collision without requiring extensive training.
How Do I Know What to Say Next? Barenholtz's Autogenerative Theory as an Enrichment of Harrisean Integrationism
Discusses the synthesis of Integrationist linguistics and autogenerative theory to provide a structural account of how LLMs exploit statistical language patterns.
Closed-Loop Dynamic Validator Node Scaling in Private Substrate Blockchains Using Takagi-Sugeno Fuzzy Inference
Implements a Takagi-Sugeno fuzzy inference system for autonomous validator node scaling in private Substrate blockchains to optimize resource usage and performance.
Mechanistic Interpretability of LLM Jailbreaks via Internal Attribution Graphs
Introduces a mechanistic interpretability framework using internal attribution graphs to diagnose and mitigate LLM jailbreaks by identifying vulnerability motifs.
Multimodal Unlearning Across Vision, Language, Video, and Audio: Survey of Methods, Datasets, and Benchmarks
A comprehensive survey on multimodal unlearning across various AI models to selectively remove sensitive or unsafe cross-modal associations.
AI-generated videos to maximally drive a target brain region
Research on using AI-generated videos to specifically target and stimulate brain regions for potential therapeutic or neurological effects.
Browser Fingerprinting – How websites track you across internet –without cookies
An explanation of browser fingerprinting techniques used by websites to track users across the internet without relying on cookies.
SHIFT: Survival Prediction from Incomplete and Heterogeneous Genomic Data
Introduction of SHIFT, a survival prediction model for genomic data that handles incomplete features without requiring test-time imputation.
Collective Intelligence with Foundation Models
A study on a multi-agent framework for cooperative reasoning, finding that model heterogeneity is the primary driver for performance gains over homogeneous setups.