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Machine Learning

[P] Trained a small BERT on 276K Kubernetes YAMLs using tree positional encoding instead of sequential

I trained a BERT-style transformer on 276K Kubernetes YAML files, replacing standard positional encoding with learned tree coordinates (d...

Reddit - Machine Learning · 1 min ·
Machine Learning

I am doing a multi-model graph database in pure Rust with Cypher, SQL, Gremlin, and native GNN looking for extreme speed and performance

Hi guys, I'm a PhD student in Applied AI and I've been building an embeddable graph database engine from scratch in Rust. I'd love feedba...

Reddit - Artificial Intelligence · 1 min ·
Llms

Chatgpt vs purpose built ai for cre underwriting: which one can finish the job?

I keep seeing people recommend chatgpt for financial modeling and I need to push back because I spent a month testing it for multifamily ...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2602.22743] Generative Data Transformation: From Mixed to Unified Data
Machine Learning

[2602.22743] Generative Data Transformation: From Mixed to Unified Data

The paper presents Taesar, a data-centric framework designed to enhance recommendation model performance by addressing data sparsity and ...

arXiv - AI · 4 min ·
[2602.22680] Toward Personalized LLM-Powered Agents: Foundations, Evaluation, and Future Directions
Llms

[2602.22680] Toward Personalized LLM-Powered Agents: Foundations, Evaluation, and Future Directions

This survey paper explores the development of personalized LLM-powered agents, focusing on their foundations, evaluation metrics, and fut...

arXiv - AI · 4 min ·
[2602.22556] Stable Adaptive Thinking via Advantage Shaping and Length-Aware Gradient Regulation
Machine Learning

[2602.22556] Stable Adaptive Thinking via Advantage Shaping and Length-Aware Gradient Regulation

The paper presents a two-stage framework for enhancing large reasoning models (LRMs) by addressing overthinking in low-complexity queries...

arXiv - AI · 3 min ·
[2602.22638] MobilityBench: A Benchmark for Evaluating Route-Planning Agents in Real-World Mobility Scenarios
Llms

[2602.22638] MobilityBench: A Benchmark for Evaluating Route-Planning Agents in Real-World Mobility Scenarios

MobilityBench introduces a benchmark for evaluating LLM-based route-planning agents, addressing challenges in real-world mobility scenari...

arXiv - AI · 4 min ·
[2602.22554] Multilingual Safety Alignment Via Sparse Weight Editing
Llms

[2602.22554] Multilingual Safety Alignment Via Sparse Weight Editing

This paper presents a novel framework for aligning safety measures in multilingual large language models (LLMs) through Sparse Weight Edi...

arXiv - Machine Learning · 3 min ·
[2602.22603] SideQuest: Model-Driven KV Cache Management for Long-Horizon Agentic Reasoning
Llms

[2602.22603] SideQuest: Model-Driven KV Cache Management for Long-Horizon Agentic Reasoning

The paper presents SideQuest, a novel model-driven approach for managing KV cache in long-horizon reasoning tasks, achieving significant ...

arXiv - Machine Learning · 3 min ·
[2602.22583] Strategy Executability in Mathematical Reasoning: Leveraging Human-Model Differences for Effective Guidance
Machine Learning

[2602.22583] Strategy Executability in Mathematical Reasoning: Leveraging Human-Model Differences for Effective Guidance

This paper explores the concept of strategy executability in mathematical reasoning, highlighting the differences between human and model...

arXiv - AI · 4 min ·
[2602.22557] CourtGuard: A Model-Agnostic Framework for Zero-Shot Policy Adaptation in LLM Safety
Llms

[2602.22557] CourtGuard: A Model-Agnostic Framework for Zero-Shot Policy Adaptation in LLM Safety

CourtGuard introduces a model-agnostic framework for zero-shot policy adaptation in LLM safety, enhancing adaptability and performance wi...

arXiv - Machine Learning · 3 min ·
[2602.22520] TEFL: Prediction-Residual-Guided Rolling Forecasting for Multi-Horizon Time Series
Machine Learning

[2602.22520] TEFL: Prediction-Residual-Guided Rolling Forecasting for Multi-Horizon Time Series

The paper presents TEFL, a novel framework for multi-horizon time series forecasting that utilizes prediction residuals to enhance accura...

arXiv - Machine Learning · 4 min ·
[2602.22508] Mirroring the Mind: Distilling Human-Like Metacognitive Strategies into Large Language Models
Llms

[2602.22508] Mirroring the Mind: Distilling Human-Like Metacognitive Strategies into Large Language Models

The paper presents Metacognitive Behavioral Tuning (MBT), a framework designed to enhance large reasoning models by incorporating human-l...

arXiv - AI · 3 min ·
[2602.22500] Mapping the Landscape of Artificial Intelligence in Life Cycle Assessment Using Large Language Models
Llms

[2602.22500] Mapping the Landscape of Artificial Intelligence in Life Cycle Assessment Using Large Language Models

This article reviews the integration of AI into life cycle assessment (LCA), highlighting trends, themes, and future directions using lar...

arXiv - AI · 4 min ·
[2602.22479] Efficient Continual Learning in Language Models via Thalamically Routed Cortical Columns
Llms

[2602.22479] Efficient Continual Learning in Language Models via Thalamically Routed Cortical Columns

This paper presents TRC², a novel architecture for continual learning in language models that mitigates catastrophic forgetting while mai...

arXiv - Machine Learning · 3 min ·
[2602.22441] How Do Latent Reasoning Methods Perform Under Weak and Strong Supervision?
Machine Learning

[2602.22441] How Do Latent Reasoning Methods Perform Under Weak and Strong Supervision?

This paper analyzes latent reasoning methods under varying supervision levels, revealing key issues like shortcut behavior and the trade-...

arXiv - Machine Learning · 4 min ·
[2602.22406] Towards Autonomous Memory Agents
Llms

[2602.22406] Towards Autonomous Memory Agents

The paper proposes autonomous memory agents that enhance LLMs by actively acquiring and curating knowledge, improving performance on benc...

arXiv - AI · 3 min ·
[2602.22302] Agent Behavioral Contracts: Formal Specification and Runtime Enforcement for Reliable Autonomous AI Agents
Nlp

[2602.22302] Agent Behavioral Contracts: Formal Specification and Runtime Enforcement for Reliable Autonomous AI Agents

The paper presents Agent Behavioral Contracts (ABC), a framework for specifying and enforcing the behavior of autonomous AI agents, addre...

arXiv - AI · 4 min ·
[2602.22287] Multi-Level Causal Embeddings
Machine Learning

[2602.22287] Multi-Level Causal Embeddings

This article presents a framework for Multi-Level Causal Embeddings, which allows for the mapping of detailed causal models into coarser ...

arXiv - Machine Learning · 3 min ·
[2602.22345] Structure and Redundancy in Large Language Models: A Spectral Study via Random Matrix Theory
Llms

[2602.22345] Structure and Redundancy in Large Language Models: A Spectral Study via Random Matrix Theory

This paper explores the reliability and efficiency of large language models (LLMs) using Random Matrix Theory. It introduces EigenTrack f...

arXiv - AI · 4 min ·
[2602.22215] Graph Your Way to Inspiration: Integrating Co-Author Graphs with Retrieval-Augmented Generation for Large Language Model Based Scientific Idea Generation
Llms

[2602.22215] Graph Your Way to Inspiration: Integrating Co-Author Graphs with Retrieval-Augmented Generation for Large Language Model Based Scientific Idea Generation

This paper introduces GYWI, a system that enhances scientific idea generation by integrating co-author knowledge graphs with retrieval-au...

arXiv - AI · 4 min ·
[2602.22286] OmniZip: Learning a Unified and Lightweight Lossless Compressor for Multi-Modal Data
Llms

[2602.22286] OmniZip: Learning a Unified and Lightweight Lossless Compressor for Multi-Modal Data

OmniZip introduces a unified and lightweight lossless compressor designed for multi-modal data, enhancing compression efficiency across v...

arXiv - Machine Learning · 4 min ·
[2602.22268] AutoQRA: Joint Optimization of Mixed-Precision Quantization and Low-rank Adapters for Efficient LLM Fine-Tuning
Llms

[2602.22268] AutoQRA: Joint Optimization of Mixed-Precision Quantization and Low-rank Adapters for Efficient LLM Fine-Tuning

The paper presents AutoQRA, a framework that optimizes mixed-precision quantization and low-rank adapters for efficient fine-tuning of la...

arXiv - Machine Learning · 4 min ·
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