Tech Meridian ← ENTITY INDEX
PROMY MERIDIAN RU

COMPANY · ENTITY #24301

Pass@K

Related event timeline, sources and context from the news index.

EVENT TIMELINE

2

RESEARCH · 1 SOURCE · arXiv cs.AI

Seq@K: an evaluation protocol for sequential feedback-driven solving by LMs

This paper introduces Seq@K, a protocol that measures whether a language model can solve a problem within K sequential attempts when given feedback after each failed attempt. Evaluated on 7 benchmarks and 16 frontier models, Seq@K often yields different model rankings than Pass@K, changes Pareto frontiers for model/configuration trade-offs, and reveals behaviors in iterative refinement and sensitivity to feedback design.

7.0

RESEARCH · 1 SOURCE · arXiv cs.AI

A comprehensive framework for all stages of large-model training (arXiv:2610.33451v1)

This arXiv preprint proposes a unified stage division and a six-dimensional analytical framework (data, objective, optimization, system constraints, evaluation, risk/governance) covering data/tokenization, pretraining, and post-training alignment for LLMs and MLLMs, systematically reviewing 395 references (2017–2026). The authors present a cross-stage effects map, a decision tree, at least ten verifiable open problems, and three core findings: scaling-law comparability depends on data quality/mixture; preference-alignment methods (RLHF, DPO) and RL with verifiable rewards shift post-training boundaries; and multimodal training challenges tokenizer design, objectives, and evaluation.

7.0