Tool-using LLM agents are mostly evaluated assuming all tools work. When a tool times out, returns a week-stale value, or has its description poisoned in deploy
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121–140 of 533Always filtered to Maschmeyer Group . Fit opens the breakdown — clear screening badges via Clear triage on the company page.
Large language models (LLMs) often produce homogeneous outputs, raising concerns that AI coding assistants may lead to convergence in the software artifacts tha
In quantum programs, Bugs4Q is a widely used benchmark containing real quantum defects. However, its evaluation assumes that benchmark labels remain valid and t
Feedback-driven loops support iterative improvement in large language models, reinforcement learning, and autonomous discovery, yet their gains often diminish u
Knowledge graph question generation (KGQG) aims to generate natural-language questions from structured graph evidence. Existing KGQG benchmarks, however, are mo
Existing architectural simulators expose aggregate metrics or raw traces, but fail to reveal complex interactions among microarchitectural events and their rela
skill.md files that stop your AI from building slop
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「說人話」:繁體中文的去 AI 味改寫 skill。抓 38 種 AI 寫作痕跡,順手校正中國用語與半形標點,給 Claude Code / Codex / Cursor 用。
Tradingview MCP server for controlling Tradingview Desktop from Claude Code via Chrome DevTools Protocol
和你的 AI 一起玩的双人棋盘小游戏 · 18+ (A two-player board game you play with your AI — dice, tiles, spicy tasks, all run by code (18+))
UXON is an MCP server and API that lets AI agents and developers create landing pages, run A/B experiments, and track conversions across domains.
A memory layer for Claude Code that learns as you work. Persistent, per-context memory as plain markdown in your own git repo. No server, no telemetry.
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Temporal Knowledge Graph (TKG) reasoning under the extrapolation setting focuses on forecasting future time-stamped events (facts) from historical data in a tem
Channel foundation models (CFMs) are developing rapidly, with recent studies reporting benefits from pretraining across downstream wireless tasks. Yet CFMs are
Context engineering has become central to building reliable AI agents, yet it remains largely unmeasured. Agents do not fail in isolation: their behavior is sha
CPUs are the most universal target for on-device LLM inference, but existing low-bit quantization methods offer either coarse operating points or fine-grained m