All Articles
17327 articles total
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.
Jet-Long: Efficient Long-Context Extension with Dynamic Bifocal RoPE
Jet-Long is a tuning-free method for extending LLM context windows using dynamic bifocal RoPE, achieving high throughput and accuracy on long-context tasks.
Architecture Generalization with MetaNCA
MetaNCA introduces a framework where neural cellular automata learn local rules to self-organize the weights of artificial neural networks without backpropagation.
A Transdiagnostic Space of Disorder Like Phenotypes in Reinforcement Learning Agents
A framework for modelling psychological disorders in RL agents by manipulating cognitive appraisal signals to study affective phenotypes.
Principled Analysis of Deep Reinforcement Learning Evaluation and Design Paradigms
A theoretical analysis of scaling laws and evaluation paradigms in deep reinforcement learning, challenging some canonical conclusions in the field.
Graph-Regularized Deep Learning for EEG-Based Emotion Recognition with Psychologically-Grounded Label Structure
A graph-regularized deep learning framework for EEG-based emotion recognition that incorporates psychologically-grounded label structures.
From Solvers to Research: Large Language Model-Driven Formal Mathematics at the Research Frontier
A position paper outlining the roadmap for transitioning LLM-driven formal mathematics from simple solvers to autonomous research agents.
Damaged Earth Catalog
A discussion thread on Hacker News regarding the Damaged Earth Catalog.
The Illusion of Equivalency: Statistical Characterization of Quantization Effects in LLMs
Research demonstrating that traditional accuracy metrics fail to capture behavioral changes in quantized LLMs, proposing a new 'correctness agreement' metric.
Workflow as Knowledge: Semantic Persistence for LLM-Mediated Workflows
A conceptual model for LLM-mediated workflows treating workflow definitions and instances as persistent, inspectable knowledge objects.
AUTOPILOT VQA: Benchmarking Vision-Language Models for Incident-Centric Dashcam Understanding
Introduction of AUTOPILOT-VQA, a benchmark for evaluating the ability of vision-language models to reason about safety-critical dashcam incidents.