Optimizing Instruction Synthesis: Effective Exploration of Evolutionary Space with Tree Search

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Li, Chenglin, Chen, Qianglong, Li, Zhi, Tao, Feng, Li, Yicheng, Chen, Hao, Yu, Fei, Zhang, Yin
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence Computation and Language
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Mixed Distillation Helps Smaller Language Model Better Reasoning
by: Li, Chenglin, et al.
Published: (2023)

Iterative Zoom-In: Temporal Interval Exploration for Long Video Understanding
by: Li, Chenglin, et al.
Published: (2025)

VideoCogQA: A Controllable Benchmark for Evaluating Cognitive Abilities in Video-Language Models
by: Li, Chenglin, et al.
Published: (2024)

MIG: Automatic Data Selection for Instruction Tuning by Maximizing Information Gain in Semantic Space
by: Chen, Yicheng, et al.
Published: (2025)

Generalizing From Short to Long: Effective Data Synthesis for Long-Context Instruction Tuning
by: Zhu, Wenhao, et al.
Published: (2025)

What are the Essential Factors in Crafting Effective Long Context Multi-Hop Instruction Datasets? Insights and Best Practices
by: Chen, Zhi, et al.
Published: (2024)

TREX: Automating LLM Fine-tuning via Agent-Driven Tree-based Exploration
by: Ma, Zerun, et al.
Published: (2026)

HunyuanProver: A Scalable Data Synthesis Framework and Guided Tree Search for Automated Theorem Proving
by: Li, Yang, et al.
Published: (2024)

An Information Bottleneck Perspective for Effective Noise Filtering on Retrieval-Augmented Generation
by: Zhu, Kun, et al.
Published: (2024)

GeoEval: Benchmark for Evaluating LLMs and Multi-Modal Models on Geometry Problem-Solving
by: Zhang, Jiaxin, et al.
Published: (2024)

IOPO: Empowering LLMs with Complex Instruction Following via Input-Output Preference Optimization
by: Zhang, Xinghua, et al.
Published: (2024)

What Factors Affect Multi-Modal In-Context Learning? An In-Depth Exploration
by: Qin, Libo, et al.
Published: (2024)

AT$^2$PO: Agentic Turn-based Policy Optimization via Tree Search
by: Zong, Zefang, et al.
Published: (2026)

Fine-grained Stateful Knowledge Exploration: Effective and Efficient Graph Retrieval with Large Language Models
by: Tao, Dehao, et al.
Published: (2024)

DeepSolution: Boosting Complex Engineering Solution Design via Tree-based Exploration and Bi-point Thinking
by: Li, Zhuoqun, et al.
Published: (2025)

Selective Expert Guidance for Effective and Diverse Exploration in Reinforcement Learning of LLMs
by: Jiang, Zishang, et al.
Published: (2025)

MineAgent: Towards Remote-Sensing Mineral Exploration with Multimodal Large Language Models
by: Yu, Beibei, et al.
Published: (2024)

Pre-training Distillation for Large Language Models: A Design Space Exploration
by: Peng, Hao, et al.
Published: (2024)

Improving Faithfulness of Large Language Models in Summarization via Sliding Generation and Self-Consistency
by: Li, Taiji, et al.
Published: (2024)

Knapsack RL: Unlocking Exploration of LLMs via Optimizing Budget Allocation
by: Li, Ziniu, et al.
Published: (2025)

Robust Search with Uncertainty-Aware Value Models for Language Model Reasoning
by: Yu, Fei, et al.
Published: (2025)

EvolVE: Evolutionary Search for LLM-based Verilog Generation and Optimization
by: Hsin, Wei-Po, et al.
Published: (2026)

LLM-First Search: Self-Guided Exploration of the Solution Space
by: Herr, Nathan, et al.
Published: (2025)

Differentiable Evolutionary Reinforcement Learning
by: Cheng, Sitao, et al.
Published: (2025)

On Leveraging Large Language Models for Enhancing Entity Resolution: A Cost-efficient Approach
by: Li, Huahang, et al.
Published: (2024)

Empirical-MCTS: Continuous Agent Evolution via Dual-Experience Monte Carlo Tree Search
by: Lu, Hao, et al.
Published: (2026)

Exploration vs Exploitation: Rethinking RLVR through Clipping, Entropy, and Spurious Reward
by: Chen, Peter, et al.
Published: (2025)

Theory of Space: Can Foundation Models Construct Spatial Beliefs through Active Exploration?
by: Zhang, Pingyue, et al.
Published: (2026)

Enhancing Multimodal Continual Instruction Tuning with BranchLoRA
by: Zhang, Duzhen, et al.
Published: (2025)

TimeBench: A Comprehensive Evaluation of Temporal Reasoning Abilities in Large Language Models
by: Chu, Zheng, et al.
Published: (2023)

SELT: Self-Evaluation Tree Search for LLMs with Task Decomposition
by: Wu, Mengsong, et al.
Published: (2025)

Countering Catastrophic Forgetting of Large Language Models for Better Instruction Following via Weight-Space Model Merging
by: Lyu, Mengxian, et al.
Published: (2026)

One-Shot Learning as Instruction Data Prospector for Large Language Models
by: Li, Yunshui, et al.
Published: (2023)

Infinity Instruct: Scaling Instruction Selection and Synthesis to Enhance Language Models
by: Li, Jijie, et al.
Published: (2025)

VideoThinker: Building Agentic VideoLLMs with LLM-Guided Tool Reasoning
by: Li, Chenglin, et al.
Published: (2026)

CO-Bench: Benchmarking Language Model Agents in Algorithm Search for Combinatorial Optimization
by: Sun, Weiwei, et al.
Published: (2025)

DataChef: Cooking Up Optimal Data Recipes for LLM Adaptation via Reinforcement Learning
by: Chen, Yicheng, et al.
Published: (2026)

Teaching According to Talents! Instruction Tuning LLMs with Competence-Aware Curriculum Learning
by: Li, Yangning, et al.
Published: (2025)

Beyond IID: Optimizing Instruction Learning from the Perspective of Instruction Interaction and Dependency
by: Zhao, Hanyu, et al.
Published: (2024)

Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future
by: Chu, Zheng, et al.
Published: (2023)