Can Harnesses Self‑Evolve? Fudan & Peking University’s Agentic Harness Engineering Breakthrough

The paper introduces Agentic Harness Engineering (AHE), showing that a 10‑round evolution improves Coding Agent pass@1 from 69.7% to 77.0% on Terminal‑Bench 2—outperforming Codex‑CLI—and that the evolved harness transfers zero‑shot to SWE‑bench and multiple model families, thanks to three observability pillars.

Ablation StudyAgentic AICoding Agent

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Can Harnesses Self‑Evolve? Fudan & Peking University’s Agentic Harness Engineering Breakthrough

Bighead's Algorithm Notes

Oct 21, 2025 · Artificial Intelligence

KANMixer: A New KAN‑Centric Paradigm for Long‑Term Time Series Forecasting

This article reviews the KANMixer model, which places Kolmogorov‑Arnold Networks at the core of a lightweight architecture for long‑term time series forecasting, detailing its design, extensive benchmark experiments on seven real‑world datasets, ablation analyses, and its computational trade‑offs versus MLP and Transformer baselines.

Ablation StudyKANLong-term Time Series Forecasting

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KANMixer: A New KAN‑Centric Paradigm for Long‑Term Time Series Forecasting

Bighead's Algorithm Notes

Oct 17, 2025 · Artificial Intelligence

Exploring MLLM4TS: A Universal Multimodal Framework for Time‑Series Analysis

This article reviews the MLLM4TS framework, which fuses visual representations of multivariate time series with large language models to address complex temporal dependencies, cross‑channel interactions, and task generalization, and demonstrates superior performance on classification, anomaly detection, forecasting, and few‑shot scenarios across multiple benchmarks.

Ablation StudyBenchmark resultsFew‑Shot Learning

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Exploring MLLM4TS: A Universal Multimodal Framework for Time‑Series Analysis

Sohu Tech Products

Dec 6, 2023 · Databases

GPTuner: LLM-Driven PostgreSQL Knob Tuning

GPTuner, an LLM‑driven system for PostgreSQL knob tuning developed by researchers at Sichuan University, demonstrates that knowledge processing, parameter selection, search‑range optimization, and a two‑stage Bayesian framework each significantly improve performance, while costing roughly 880 000 GPT‑4 tokens (≈ $30) with reusable knowledge.

Ablation StudyDatabase TuningGPTuner

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GPTuner: LLM-Driven PostgreSQL Knob Tuning