AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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Results show that a conceptually coherent chain and a correct final answer do not by themselves establish multi-hop reasoning, and introduce REALHOP, a diagnose-construct-verify framework that rebinds entities, factorizes selected relations, adds complete competing paths, and places evidence at traceable locations.
Real-Q (Real-time E2E-loss Aligned LLM Quantization), a novel PTQ paradigm that breaks this compromise: instead of diluting the objective for the sake of analytic tractability, REAL-Q targets an end-to-end-aligned surrogate of the global loss and refines it via fine-grained, dynamic Block-wise Gradient Descent applied...
The first fully automated framework that synthesizes high-quality, proof-centric benchmarks from natural language mathematical corpora and a new type of hybrid-formatted questions, named ``$m$-out-of-$n$ multiple judge questions'', specifically designed to enable robust, automatic evaluation while being resilient to gu...
Benchmark saturation and data contamination increasingly obscure genuine scientific reasoning in frontier LLMs. We introduce \textsc{ScienceArena}, an olympiad-style benchmark from thirteen public science competitions in physics, chemistry, and biology, including IPhO and IChO 2025--2026, IBO 2023, USAPhO 2026, and USN...
ReQuant is introduced, a backpropagation-free fixed-grid refinement procedure that takes an existing quantized model as a feasible starting point and iteratively revisits its discrete weight assignments on the fixed quantization grid, and turns the initially fixed PTQ output into an iteratively optimizable discrete sol...
RealClawBench is introduced, a live benchmark framework built from real OpenClaw sessions to capture the distribution, diversity, and real-world difficulty of deployed agent use and provides a practical path toward benchmarks that better measure agent capability in actual use.
This work introduces ArborMem, an online memory framework that represents a long-running conversation as a navigable forest of interaction states that outperforms the strongest baselines on three established benchmarks and introduces BranchMemEval, a controlled diagnostic benchmark for interleaved and resumable interac...
This work analyzes real chatbot failures to identify six recurring mechanisms and defines six controlled evaluation modes in Hy-MultiTurn, a Chinese benchmark for deep multi-turn dialogue understanding, which shows that Hy-MultiTurn is broadly challenging.
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