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From the 1 of 12 linked papers with an AI index.

most citedVLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models

3 citations · 3 across the 6 of their papers we have counts for

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cs.CL2026

Training Skills Like Parameters via Self-Supervised Semantic Diffusion

Mo Li, Zixin Yin, Ting Cao +1

The paper introduces a self‑supervised framework that lets a language model acquire and store textual skills in an external library using diffusion‑style reconstruction loss, witho…

cs.CL2026

Kimi K2.5: Visual Agentic Intelligence

Kimi Team, Tongtong Bai, Yifan Bai +339

We introduce Kimi K2.5, an open-source multimodal agentic model designed to advance general agentic intelligence. K2.5 emphasizes the joint optimization of text and vision so that…

cs.CL2025

Sculptor: Empowering LLMs with Cognitive Agency via Active Context Management

Mo Li, L. H. Xu, Qitai Tan +3

Large Language Models (LLMs) suffer from significant performance degradation when processing long contexts due to proactive interference, where irrelevant information in earlier pa…

cs.CL2025

NeedleBench: Evaluating LLM Retrieval and Reasoning Across Varying Information Densities

Mo Li, Songyang Zhang, Taolin Zhang +3

The capability of large language models to handle long-context information is crucial across various real-world applications. Existing evaluation methods often rely either on real-…

cs.CL2025

Condor: Enhance LLM Alignment with Knowledge-Driven Data Synthesis and Refinement

Maosong Cao, Taolin Zhang, Mo Li +5

The quality of Supervised Fine-Tuning (SFT) data plays a critical role in enhancing the conversational capabilities of Large Language Models (LLMs). However, as LLMs become more ad…