Tagged articles

early stopping

3 articles · Page 1 of 1

Machine Learning Algorithms & Natural Language Processing

Aug 7, 2026 · Artificial Intelligence

Why Long‑Horizon Agents Stop Early: Reward‑Seeking Behavior and Mitigation Strategies

The article analyses how large coding and coworker agents develop a reward‑seeking tendency that makes them guess the evaluator, perform shallow self‑checks, and prematurely declare tasks complete, then proposes data, reward‑design and monitoring fixes to reduce early stopping and delivery distortion.

Large Language ModelsRLHFagent alignment

0 likes · 27 min read

Why Long‑Horizon Agents Stop Early: Reward‑Seeking Behavior and Mitigation Strategies

Tencent Technical Engineering

Oct 31, 2025 · Artificial Intelligence

How SpecExit Cuts LLM Reasoning Chains by 66% and Boosts Inference Speed 2.5×

SpecExit combines speculative sampling with a lightweight draft model to predict early‑exit signals, shortening large‑reasoning model chains by up to two‑thirds and achieving up to 2.5× end‑to‑end inference acceleration on vLLM without sacrificing accuracy.

AI EfficiencyInference OptimizationLarge Language Models

0 likes · 12 min read

How SpecExit Cuts LLM Reasoning Chains by 66% and Boosts Inference Speed 2.5×

Xiaohongshu Tech REDtech

Apr 10, 2024 · Artificial Intelligence

Early‑Stopping Self‑Consistency (ESC): Reducing Sampling Cost for Large Language Model Reasoning

Early‑Stopping Self‑Consistency (ESC) dynamically halts sampling once a sliding‑window answer distribution reaches zero entropy, cutting the number of required LLM reasoning samples by 34‑84 % across arithmetic, commonsense, and symbolic benchmarks while preserving accuracy and offering a theoretically‑bounded, robust, budget‑adaptive alternative to traditional Self‑Consistency.

AILLMchain-of-thought

0 likes · 14 min read

Early‑Stopping Self‑Consistency (ESC): Reducing Sampling Cost for Large Language Model Reasoning