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20152026
most citedKnowledge forest: a novel model to organize knowledge fragments

5 citations · 11 across the 14 of their papers we have counts for

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6 papers · 1 filter

cs.AI2026

CVIF: A Criticality-Driven Visual Intervention Framework for Geometric Diagram Understanding in MLLMs

Jiahui Kang, Bifan Wei, Lingling Zhang +4

Despite significant progress in visual tasks by Multimodal Large Language Models (MLLMs), geometric diagram understanding remains challenging due to the presence of sparse visual c…

cs.CL2026

Dual-Cluster Memory Agent: Resolving Multi-Paradigm Ambiguity in Optimization Problem Solving

Xinyu Zhang, Yuchen Wan, Boxuan Zhang +4

Large Language Models (LLMs) often struggle with structural ambiguity in optimization problems, where a single problem admits multiple related but conflicting modeling paradigms, h…

cs.AI2026

Beyond Individual Intelligence: Surveying Collaboration, Failure Attribution, and Self-Evolution in LLM-based Multi-Agent Systems

Shihao Qi, Jie Ma, Rui Xing +15

LLM-based autonomous agents have demonstrated strong capabilities in reasoning, planning, and tool use, yet remain limited when tasks require sustained coordination across roles, t…

cs.CL2026

OptiVerse: A Comprehensive Benchmark towards Optimization Problem Solving

Xinyu Zhang, Boxuan Zhang, Yuchen Wan +5

While Large Language Models (LLMs) demonstrate remarkable reasoning, complex optimization tasks remain challenging, requiring domain knowledge and robust implementation. However, e…

cs.LG2026

$\textbf{AGT$^{AO}$}$: Robust and Stabilized LLM Unlearning via Adversarial Gating Training with Adaptive Orthogonality

Pengyu Li, Lingling Zhang, Zhitao Gao +5

While Large Language Models (LLMs) have achieved remarkable capabilities, they unintentionally memorize sensitive data, posing critical privacy and security risks. Machine unlearni…

cs.AI2026

ErrEval: Error-Aware Evaluation for Question Generation through Explicit Diagnostics

Weiping Fu, Bifan Wei, Jingyi Hao +7

Automatic Question Generation (QG) often produces outputs with critical defects, such as factual hallucinations and answer mismatches. However, existing evaluation methods, includi…