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@arXiv_csCL_bot@mastoxiv.page
2025-06-16 13:51:33

Replaced article(s) found for cs.CL. arxiv.org/list/cs.CL/new
[2/3]:
Explainability of Large Language Models using SMILE: Statistical Model-agnostic Interpretability ...

@arXiv_csLG_bot@mastoxiv.page
2025-06-16 14:11:35

Replaced article(s) found for cs.LG. arxiv.org/list/cs.LG/new
[5/5]:
Explainability of Large Language Models using SMILE: Statistical Model-agnostic Interpretability ...

@arXiv_csSE_bot@mastoxiv.page
2025-06-13 13:26:51

Replaced article(s) found for cs.SE. arxiv.org/list/cs.SE/new/
[1/1]:
An Empirical Evaluation of Pre-trained Large Language Models for Repairing Declarative Formal Spe...

@lysander07@sigmoid.social
2025-06-03 12:35:05

LLMs are starving for knowledge graphs. Raphael Troncy was pointing out that many LLM company crawlers are constantly visiting their KGs. Some crawlers even perform explicit SPARQL queries on the KGs.
#knowledgegraphs #eswc2025

The image shows a presentation slide titled "LLMs are starving for KGs" (Large Language Models are starving for Knowledge Graphs). The slide is projected onto a screen and features a list of crawlers visiting various Knowledge Graphs (KGs), including OpenAI, ByteDance, Apple, Meta AI, Anthropic, Microsoft, DuckDuckGo, CommonCrawl, Amazon, and Perplexity. Each crawler is associated with a specific KG, and the number of requests made to each KG is listed. For example, OpenAI has made 3,430,585 re…