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20242026
most citedAn Investigation into the Performance of Non-Contrastive Self-Supervised Learning Methods for Network Intrusion Detection

2 citations · 5 across the 12 of their papers we have counts for

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Showing 2026 · cs.CLShow all

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cs.CL2026

Prompt Compression via Activation Aggregation

Thibaud Ardoin, Semira Einsele, Evis Bregu +1

Large language models process prompts by propagating activations through dozens of layers before generating a response. We ask whether the task-relevant information contained in an…

cs.CL2026

Robust Text Watermarking for Large Language Models via Dual Semantic Embeddings

Jonas Schäfer, Cezary Pilaszewicz, Gerhard Wunder

This work presents Dual-Embedding Watermarking (DEW), a semantic watermarking scheme for large language models (LLMs) that leverages contextual and token-level embeddings to enhanc…