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Ai Agents

AI agents have been blindly guessing your UI this whole time. Here's the file that fixes it.

Every time you ask an AI coding agent to build UI, it invents everything from scratch. Colors. Fonts. Spacing. Button styles. All of it -...

Reddit - Artificial Intelligence · 1 min ·
Llms

OpenClaw security checklist: practical safeguards for AI agents

Here is one of the better quality guides on the ensuring safety when deploying OpenClaw: https://chatgptguide.ai/openclaw-security-checkl...

Reddit - Artificial Intelligence · 1 min ·
Machine Learning

Auto agent - Self improving domain expertise agent

someone opensource an ai agent that autonomously upgraded itself to #1 across multiple domains in < 24 hours…. then open sourced the e...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2602.18495] RDBLearn: Simple In-Context Prediction Over Relational Databases
Machine Learning

[2602.18495] RDBLearn: Simple In-Context Prediction Over Relational Databases

RDBLearn introduces a novel approach for in-context learning (ICL) in relational databases, enabling efficient prediction tasks without e...

arXiv - Machine Learning · 3 min ·
[2602.19355] Active perception and disentangled representations allow continual, episodic zero and few-shot learning
Machine Learning

[2602.19355] Active perception and disentangled representations allow continual, episodic zero and few-shot learning

This paper presents a Complementary Learning System (CLS) that enables continual, episodic zero and few-shot learning by utilizing active...

arXiv - AI · 4 min ·
[2602.18481] AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models
Llms

[2602.18481] AlphaForgeBench: Benchmarking End-to-End Trading Strategy Design with Large Language Models

The paper introduces AlphaForgeBench, a framework for evaluating trading strategies using Large Language Models (LLMs), addressing issues...

arXiv - AI · 4 min ·
[2602.19345] Smooth Gate Functions for Soft Advantage Policy Optimization
Llms

[2602.19345] Smooth Gate Functions for Soft Advantage Policy Optimization

This paper explores Smooth Gate Functions for Soft Advantage Policy Optimization, enhancing the stability of large language model trainin...

arXiv - Machine Learning · 3 min ·
[2602.18479] AgentCAT: An LLM Agent for Extracting and Analyzing Catalytic Reaction Data from Chemical Engineering Literature
Llms

[2602.18479] AgentCAT: An LLM Agent for Extracting and Analyzing Catalytic Reaction Data from Chemical Engineering Literature

AgentCAT is a large language model designed to extract and analyze catalytic reaction data from chemical engineering literature, addressi...

arXiv - AI · 4 min ·
[2602.18476] BioLM-Score: Language-Prior Conditioned Probabilistic Geometric Potentials for Protein-Ligand Scoring
Machine Learning

[2602.18476] BioLM-Score: Language-Prior Conditioned Probabilistic Geometric Potentials for Protein-Ligand Scoring

BioLM-Score introduces a novel protein-ligand scoring model that enhances efficiency and interpretability in drug design by integrating g...

arXiv - Machine Learning · 4 min ·
[2602.19327] Soft Sequence Policy Optimization: Bridging GMPO and SAPO
Llms

[2602.19327] Soft Sequence Policy Optimization: Bridging GMPO and SAPO

The paper introduces Soft Sequence Policy Optimization, a new approach to policy optimization in reinforcement learning that enhances tra...

arXiv - Machine Learning · 3 min ·
[2602.19289] AdsorbFlow: energy-conditioned flow matching enables fast and realistic adsorbate placement
Generative Ai

[2602.19289] AdsorbFlow: energy-conditioned flow matching enables fast and realistic adsorbate placement

The paper introduces AdsorbFlow, a deterministic generative model that enhances the efficiency of adsorbate placement on catalytic surfac...

arXiv - Machine Learning · 4 min ·
[2602.18471] Charting the Future of AI-supported Science Education: A Human-Centered Vision
Ai Infrastructure

[2602.18471] Charting the Future of AI-supported Science Education: A Human-Centered Vision

This article discusses the transformative potential of AI in science education, proposing a human-centered framework for its ethical inte...

arXiv - AI · 4 min ·
[2602.19261] DGPO: RL-Steered Graph Diffusion for Neural Architecture Generation
Machine Learning

[2602.19261] DGPO: RL-Steered Graph Diffusion for Neural Architecture Generation

The paper presents DGPO, a method for neural architecture generation using reinforcement learning to optimize directed graph diffusion mo...

arXiv - AI · 4 min ·
[2602.18470] Transforming Science Learning Materials in the Era of Artificial Intelligence
Generative Ai

[2602.18470] Transforming Science Learning Materials in the Era of Artificial Intelligence

This article explores how AI is reshaping science learning materials, enhancing personalization, accessibility, and interactivity while a...

arXiv - AI · 4 min ·
[2602.19265] Spectral bias in physics-informed and operator learning: Analysis and mitigation guidelines
Machine Learning

[2602.19265] Spectral bias in physics-informed and operator learning: Analysis and mitigation guidelines

This paper explores spectral bias in physics-informed neural networks and operator learning, analyzing its causes and offering mitigation...

arXiv - Machine Learning · 4 min ·
[2602.19237] Evaluating SAP RPT-1 for Enterprise Business Process Prediction: In-Context Learning vs. Traditional Machine Learning on Structured SAP Data
Llms

[2602.19237] Evaluating SAP RPT-1 for Enterprise Business Process Prediction: In-Context Learning vs. Traditional Machine Learning on Structured SAP Data

This article evaluates SAP's RPT-1 model for enterprise business process prediction, comparing its performance against traditional machin...

arXiv - AI · 4 min ·
[2602.18469] The Landscape of AI in Science Education: What is Changing and How to Respond
Ai Infrastructure

[2602.18469] The Landscape of AI in Science Education: What is Changing and How to Respond

This article explores the transformative impact of AI on science education, highlighting changes in educational practices and the need fo...

arXiv - AI · 4 min ·
[2602.18466] Can Multimodal LLMs See Science Instruction? Benchmarking Pedagogical Reasoning in K-12 Classroom Videos
Llms

[2602.18466] Can Multimodal LLMs See Science Instruction? Benchmarking Pedagogical Reasoning in K-12 Classroom Videos

This article evaluates the effectiveness of multimodal large language models (LLMs) in analyzing K-12 science classroom discourse, reveal...

arXiv - AI · 4 min ·
[2602.18464] How Well Can LLM Agents Simulate End-User Security and Privacy Attitudes and Behaviors?
Llms

[2602.18464] How Well Can LLM Agents Simulate End-User Security and Privacy Attitudes and Behaviors?

This paper investigates the effectiveness of large language model (LLM) agents in simulating user attitudes and behaviors towards securit...

arXiv - AI · 4 min ·
[2602.19208] How to Allocate, How to Learn? Dynamic Rollout Allocation and Advantage Modulation for Policy Optimization
Llms

[2602.19208] How to Allocate, How to Learn? Dynamic Rollout Allocation and Advantage Modulation for Policy Optimization

This article presents DynaMO, a novel framework for optimizing reinforcement learning with verifiable rewards, addressing key challenges ...

arXiv - AI · 4 min ·
[2602.18460] The Doctor Will (Still) See You Now: On the Structural Limits of Agentic AI in Healthcare
Robotics

[2602.18460] The Doctor Will (Still) See You Now: On the Structural Limits of Agentic AI in Healthcare

This article examines the limitations of agentic AI in healthcare, highlighting the gap between commercial promises and operational reali...

arXiv - AI · 4 min ·
[2602.19187] Adaptive Problem Generation via Symbolic Representations
Llms

[2602.19187] Adaptive Problem Generation via Symbolic Representations

This article presents a novel method for generating training data for reinforcement learning using symbolic representations, enhancing th...

arXiv - Machine Learning · 3 min ·
[2602.19172] Online Realizable Regression and Applications for ReLU Networks
Machine Learning

[2602.19172] Online Realizable Regression and Applications for ReLU Networks

This paper explores realizable online regression in adversarial settings, highlighting its differences from online classification and int...

arXiv - Machine Learning · 4 min ·
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