Small and Efficient Mathematical Reasoning LLMs
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Jan 27, 2024 - Python
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Small and Efficient Mathematical Reasoning LLMs
[ACL 2023] Solving Math Word Problems via Cooperative Reasoning induced Language Models (LLMs + MCTS + Self-Improvement)
Reproducible Language Agent Research
DICE: Detecting In-distribution Data Contamination with LLM's Internal State
Fast runtime for Random Optimization at scale.
GRPO and SFT Finetune Qwen3 using Unsloth : Reasoning and Non-Reasoning Dataset
Prompt-engineering study on LLM math reasoning (GSM8K) and code generation (HumanEval): zero/few-shot, self-consistency, self-verification, and experiments on prompt quality, complexity, demonstrations, and diversity.
CS336 作业 5:基于 Qwen2.5 模型的 LLM 对齐与推理强化学习。完整实现了监督微调(SFT)与组相对策略优化(GRPO)算法,并在 GSM8K 数据集上完成零样本、在策与离策的训练与评估对比。
Short-CoT distilled GSM8K dataset generated with OpenAI gpt-oss-120b.
OpenCompass evaluation harness inspired by Agent0, with reproducible GPT-4o-mini runs on GSM8K and MATH; co-training is not yet implemented.
GSM8K-Consistency is a benchmark database for analyzing the consistency of Arithmetic Reasoning on GSM8K.
Hard Reasoning Benchmark filtered with disagreement scores
Reproduction & re-implementation of the AloLab paper (arXiv:2605.02363): closing the structured-output reliability gap in small LLMs via iterative black-box prompt optimization. GSM8K, 4 models, ablations, McNemar significance.
A controlled LoRA finetuning study on process supervision for mathematical reasoning with Qwen2.5-Math-7B-Instruct.
An evaluation of prompting techniques (Zero-Shot CoT, Few-Shot, Self-Consistency) on the Mistral-7B model for mathematical reasoning. This project systematically benchmarks 7 distinct methods on the GSM8K dataset.
Code and results for consistency-gated self-correction in large language model reasoning.
大模型评测平台 — 本地/API/HuggingFace/OpenCompass 三路后端,支持数据生产(Self-Instruct/Evol-Instruct)、长尾场景生成、弱项挖掘、回归分析、污染检测、Bad Case归因。可扩展的 Benchmark 系统和 LLM-as-Judge 自动评分。
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