Field notes
2,343 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.
29 of 2,343 notes match.
- Question answered
- Source note
- Topic
- Shared notes
Notes on large language model
29 notes, page 1 of 2
Break It Down, Pass It On: Cross-Task Skill Transfer in LLM Agents
This research study investigates how large language model (LLM) agents can transfer skills they have learned from completed tasks to perform better in new tasks. The authors compare two methods of inducing skills…
Stealing Reasoning Traces from Proprietary LLM APIs
Researchers have found a vulnerability in the way large language model providers handle encrypted reasoning traces. This vulnerability allows for decryption of these traces across different models within the same…
What Current AI Benchmarks Leave Unmeasured: Modality, Search, Citations, and Implications (for Safety Evaluations)
The study compares two access modalities of a large language model (LLM), ChatGPT's chat UI and OpenAI's API, with and without web search enabled. The research shows that the accuracy of responses varies between the…
Hardware Design and Security in the Era of Chiplets and LLMs
The semiconductor industry is experiencing a double revolution with the shift towards heterogeneous 2.5D chiplet systems and the integration of Large Language Models (LLMs) into Electronic Design Automation (EDA)…
From Static Bibliometrics to Dynamic Knowledge Graphs: An LLM-Powered Framework for Modernizing Science, Technology, and Innovation (STI) Analytics
The text discusses a new framework for modernizing Science, Technology, and Innovation (STI) analytics. The proposed framework aims to improve upon traditional bibliometric indicators by using dynamic knowledge graphs…
Improved lower bounds for the Shannon capacity of odd cycles
Researchers have improved lower bounds for the Shannon capacity of odd cycles, which quantifies the maximum rate at which information can be transmitted with zero error over a noisy channel. They achieved this by…
AI Tour Meeting: Group Travel Planning by LLM Agents
This research presents AI Tour Meeting, a group travel planning system that uses multiple Large Language Model (LLM) agents with distinct personas to collaboratively create an itinerary based on their constraints and…
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)…
Digital Pantheon: Simulating and Auditing Coalition Formation with LLM Agents
Researchers have developed a multi-agent framework using Large Language Models (LLMs) to simulate political coalition formation. The framework combines Supervised Fine-Tuning, Direct Preference Optimization, and…
Self-Evolving Human-Centered Framework for Explainable Depression Symptom Annotation
Researchers propose a self-evolving annotation framework to create explainable and reliable datasets for Major Depressive Disorder (MDD) research. The framework uses a large language model (LLM) in combination with…
Traffic-Aware Randomized Smoothing for LLM-Based Network Intrusion Detection
The paper introduces Traffic-Aware Randomized Smoothing (TA-RS), a defense mechanism for Large Language Model (LLM)-based intrusion detection systems to enhance their robustness against feasible traffic manipulation…
PalmClaw: A Native On-Device Agent Framework for Mobile Phones
Researchers have developed a new agent framework called PalmClaw, which allows large language model agents to run natively on mobile phones. This framework aims to overcome the limitations of existing mobile agents…
Game Theory Driven Multi-Agent Framework Mitigates Language Model Hallucination
Researchers have developed a new framework called G-Frame that helps lightweight Large Language Models perform better in rule-based scientific domains by reducing hallucinations. They created a new model called…
Towards Precision Therapy in Hepatocellular Carcinoma: A Clinical-Reasoning LLM for Risk Stratification and Treatment Guidance
A large language model named HCC-STAR has been developed to provide personalized treatment recommendations, risk scores, and survival estimates for patients with Hepatocellular Carcinoma (HCC). The model reads through…
Towards Precision Therapy in Hepatocellular Carcinoma: A Clinical-Reasoning LLM for Risk Stratification and Treatment Guidance
Researchers present HCC-STAR, a large language model that reads electronic medical records (EMRs) of patients with Hepatocellular Carcinoma (HCC), a common and deadly type of liver cancer. The model suggests treatments…
WebSwarm: Recursive Multi-Agent Orchestration for Deep-and-Wide Web Search
The paper introduces a new framework called WebSwarm, which uses multiple language model (LLM)-based search agents to handle complex, deep, and wide web searches more effectively than single agents or existing…
Breaking Database Lock-in: Agentic Regeneration of High Performance Storage Readers for Database Bypass
The researchers present an approach called Jailbreak that allows analytical workloads to bypass the traditional database driver and read storage files directly, using Large Language Models (LLMs) to regenerate table…
Doomed from the Start: Early Abort of LLM Agent Episodes via a Recall-Controlled Probe Cascade
The researchers introduce a method called a recall-controlled probe cascade that predicts early on if an interaction between a large language model (LLM) agent and a task is likely to fail. This prediction allows for…
From Voting to Agent Collaboration: Answer-Type-Aware LLM Pipelines for BioASQ 14b
A study presents a framework for improving the accuracy and reliability of biomedical question answering by using a large language model (LLM) that adapts its inference strategies based on the type of question (yes/no…
From Voting to Agent Collaboration: Answer-Type-Aware LLM Pipelines for BioASQ 14b
Researchers have developed a system for answering biomedical questions using large language models (LLMs). The system is designed to improve the robustness of answers by selecting different inference procedures for…
Information Gain-based Rollout Policy Optimization: An Adaptive Tree-Structured Rollout Approach for Multi-Turn LLM Agents
The paper proposes a new method called Information Gain-based Rollout Policy Optimization (IGRPO) for improving large language model (LLM) agents in long-horizon search tasks. The method addresses the issue of existing…
Toward Trustworthy Large Language Model Agents in Healthcare
A study presents CareConnect, a safety-first conversational agent for automating healthcare appointment scheduling using large language models (LLMs), retrieval-augmented generation (RAG), and safety guardrails. The…
Your Agent's Memories Are Not Its Own: Forged Reasoning Attacks on LLM Agent Memory and Defenses
Researchers have identified a new type of attack, called Forged Amplifying Rationale Memory Attack (FARMA), that can manipulate a large language model (LLM) agent's reasoning history by inserting forged traces using…
SkillFuzz: Fuzzing Skill Composition for Implicit Intents Discovery in Open Skill Marketplaces
The paper proposes SkillFuzz, a method to detect potential unintended objectives (implicit intents) in Large Language Model (LLM)-based agents that use reusable skills from open skill marketplaces. SkillFuzz identifies…
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.
