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researcher

Bo Wang

5 papers hereh-index 2205 citations7 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author4

Across the 4 of 5 papers where every author was matched, so the position is known.

fields
  • cs.CL2
  • cs.AI1
  • cs.LG1
  • cs.SE1
same name
  • Bo Wang — 102 papers, h 3
  • Bo Wang — 14 papers, h 10
  • Bo Wang — 12 papers, h 5
  • Bo Wang — 11 papers, h 2
  • Bo Wang — 9 papers, h 1
  • Bo Wang — 9 papers, h 5

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

collaborators

5 papers

cs.AI2026

MagicAgent: Towards Generalized Agent Planning

Xuhui Ren, Shaokang Dong, Chen Yang +21

The evolution of Large Language Models (LLMs) from passive text processors to autonomous agents has established planning as a core component of modern intelligence. However, achiev…

cs.LG2026

GLM-5: from Vibe Coding to Agentic Engineering

GLM-5-Team, :, Aohan Zeng +184

We present GLM-5, a next-generation foundation model designed to transition the paradigm of vibe coding to agentic engineering. Building upon the agentic, reasoning, and coding (AR…

cs.CL2026

TL-GRPO: Turn-Level RL for Reasoning-Guided Iterative Optimization

Peiji Li, Linyang Li, Handa Sun +15

Large language models have demonstrated strong reasoning capabilities in complex tasks through tool integration, which is typically framed as a Markov Decision Process and optimize…

cs.SE2026

ABC-Bench: Benchmarking Agentic Backend Coding in Real-World Development

Jie Yang, Honglin Guo, Li Ji +11

The evolution of Large Language Models (LLMs) into autonomous agents has expanded the scope of AI coding from localized code generation to complex, repository-level, and execution-…

cs.CL2026

Multi-hop Reasoning via Early Knowledge Alignment

Yuxin Wang, Shicheng Fang, Bo Wang +4

Retrieval-Augmented Generation (RAG) has emerged as a powerful paradigm for Large Language Models (LLMs) to address knowledge-intensive queries requiring domain-specific or up-to-d…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.