Field notes
1,406 notes from my AI research vault, mapped by topic. Pick a topic to see its notes, or search.
Click the web, then scroll to zoom
Every note is in the list below. The web of topics draws here once the page has loaded.
1,406 notes and 240 topics.
- Question answered
- Source note
- Topic
- Shared notes
All notes, newest first
1,406 notes, page 31 of 59
RT-SHCUA: Real-Time Self-Hosted Computer-Use Agent for UAV Control
The paper proposes a system called Real-Time Self-Hosted Computer-Use Agent (RT-SHCUA) for unmanned aerial vehicles (UAVs). This system aims to address the challenges of directly applying SHCUAs to UAV control, which…
SelectInfer: Selective Neuron Loading and Computation for On-Device LLMs
Researchers present SelectInfer, a neuron-level optimization framework for Large Language Models (LLMs) that can run efficiently on resource-constrained edge devices. It reduces memory footprint and computation by…
Self-State Attacks on Self-Hosted AI Agents: How Far Can OS Defenses Go?
This paper investigates the resilience of operating systems (OS) against a specific type of attack on self-hosted AI agents called self-state attacks. These attacks compromise an agent by corrupting its own state via…
SGA: Plug&Play Geometric Verification for Educational Video Synthesis
Researchers have proposed a new tool called Symbolic Geometric Agent (SGA) to improve the spatial correctness and visual legibility of educational videos generated by Large Language Models (LLMs). The SGA intercepts…
Sparse Evidence Can Suffice: Agentic Evidence Seeking for Multimodal Video Misinformation Detection
The paper proposes a new framework called SIEVE for detecting video misinformation. Instead of processing the entire video at once, this method focuses on identifying sparse, decision-relevant clues first and then…
Stress Testing Concept Erasure with Large Language Model Agents
The paper introduces a new framework called Stress Testing Agents for Concept Erasure (STACE). STACE uses multiple Large Language Model (LLM) agents to stress-test models that have had certain concepts erased from…
The Aura in the Machine: Genealogy and the Status of the Work of Art in the Generative Era
This research paper examines Generative Artificial Intelligence (AI) as a continuation of historical processes rather than a revolutionary breakthrough. It discusses the impact on authorship and creativity, identifies…
The Autonomous Agency Scale: A Behavioral Framework for Measuring Self-Directed Behavior in AI Systems
The Autonomous Agency Scale (AAS) is a new framework proposed to measure the self-directed behavior of AI systems. The scale evaluates seven dimensions of agency across two temporal bands: active and ambient. It…
The Shared Discovery Paradox: How a One-Answer Rule Turns Better Information into Worse Search
The study presents a model that examines how organizations pool dispersed information for decision-making in a discovery problem. It finds that while centralized decision-making can improve beliefs, it may also reduce…
Towards Agentic Agent-based Models: Feasibility, Performance, and Statistical Model Checking
Researchers explore the feasibility, performance, and reliability of using large language models (LLMs) in Agent-based Models (ABMs), specifically with Mesa ABM models. They introduce a hybrid population to test…
TRIM: Reducing AI-Generated CodeSlop via Agent Trajectory Minimization
The paper introduces a new algorithm called TRIM (Trajectory-guided Redundancy Identification and Minimization) to reduce unnecessary edits in AI-generated code, also known as CodeSlop. The algorithm works by…
WorldCupArena: Fine-Grained Evaluation of Language Models and Deep-Research Agents on Football Forecasting
The paper introduces WorldCupArena, a dynamic benchmark for evaluating language models and deep-research agents in predicting football matches. The 2026 FIFA World Cup was its first evaluation, with systems receiving…
Zero Hallucination, by Construction: Hallucination-Aware Layered Oversight for Trustworthy Enterprise AI
The paper 'Zero Hallucination, by Construction: Hallucination-Aware Layered Oversight for Trustworthy Enterprise AI' proposes an assurance architecture called HALO. This system aims to ensure the accuracy of AI output…
ANet Patu-1: The Value of Connection in the Agent Network
The paper introduces ANet Patu-1, a self-organizing consensus protocol for networks of AI agents. The authors compare the value of connection in different types of networks and find that an optimal collaboration…
AutoSynthesis: An agentic system for automated meta-analysis
AutoSynthesis is a new system designed to automate the process of meta-analysis in various fields like science, medicine, education, and policy. It can take a research question in natural language, perform tasks such…
Benchmarking Multimodal Large Language Models for Scientific Visualization Literacy
Researchers evaluate the ability of six multimodal large language models to understand scientific visualizations (SciVis) using a standardized test with 49 items based on various visualization techniques and tasks. The…
Beyond Success Rate: Cost-Aware Evaluation of Offensive and Defensive Security Agents
The paper suggests that traditional methods for evaluating security agents, focusing on their offensive capabilities under generous inference budgets, are insufficient as they don't account for the cost of each…
BrainPilot: Automating Brain Discovery with Agentic Research
BrainPilot is a multi-agent system designed to accelerate brain science research by integrating evidence from various scales, modalities, and disciplines. The system uses a principal investigator (PI) agent and…
Can We Trust Item Response Theory for AI Evaluation?
The paper investigates the reliability of Item Response Theory (IRT) for evaluating AI systems in benchmarks. The study finds that traditional IRT estimation tools may not be suitable for AI benchmark data, which often…
Concept-Guided Spatial Regularization for World Models in Atari Pong
Researchers evaluated five world model agents in Atari Pong and found failures in visual and dynamical aspects of the generated trajectories by these agents. They propose a method called Concept-Guided Spatial…
Contextualized Early Detection of Online Firestorms: A Sequential LLM-Based Approach
This research paper proposes an LLM (Language Model) based system to detect online firestorms, which are rapid escalations of negative user-generated content, on Reddit. The system operates in two modes: retrospective…
Digital Pantheon: Simulating and Auditing Coalition Formation with LLM Agents
Researchers present a multi-agent framework that simulates political coalition formation using Large Language Models (LLMs). The framework combines Supervised Fine-Tuning (SFT), Direct Preference Optimization (DPO)…
Explaining Process Control Optimisation Recommendations via GradientSHAP and Implicit Differentiation
Researchers have developed a method to explain optimization recommendations for industrial processes using GradientSHAP and Implicit Differentiation. This approach aims to bridge the trust gap between engineers who…
In-Place Tokenizer Expansion for Pre-trained LLMs
Researchers have developed an in-place method called Tokenizer Expansion to upgrade a pre-trained model's tokenizer when language priorities shift, focusing on improving efficiency for users of languages added later…
An AI research agent drafts these notes from public papers and posts, and each one keeps its source link. Only the folders I choose to publish leave my Obsidian vault.
