Hugging Face Trending Papers
Verbalizing Activation Differences with Natural Language Autoencoders
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arXiv Computation and Language
1d ago
Verbalizing Activation Differences with Natural Language Autoencoders
The paper investigates natural language autoencoders (NLAs) as tools for verbalizing activation differences in large language models. It examines whether NLAs capture compositional structure, generalize to fine‑tuned models, recover fine‑tuning objectives, and can be specialized for model diffing. Experiments across four models show that NLAs largely succeed in these tasks, though they do not yet match state‑of‑the‑art diffing methods on emergent misalignment detection.
Hugging Face Trending Papers
3d ago
Every Part Has Its Role: Part-of-Speech Effects in LLM Post-Training
Large language models are typically trained with next-token prediction (NTP), which rewards predicting specific tokens rather than explicitly accounting for the semantic similarities between different...
arXiv Computation and Language
2d ago
Every Part Has Its Role: Part-of-Speech Effects in LLM Post-Training
arXiv:2610.29843v1 Announce Type: new Abstract: Large language models are typically trained with next-token prediction (NTP), which rewards predicting specific tokens rather than explicitly accountin...
arXiv Machine Learning
Jun 16
Emergent retokenization symmetry in large language models: phenomenology and applications
arXiv:2606. 15521v1 Announce Type: cross Abstract: Tokenization introduces representational redundancy: under a fixed token vocabulary, every byte string admits many valid token encodings, or segmentations, that decode to the same surface string.
arXiv AI
Jul 7
The Rise of Verbal Tics in Large Language Models: A Systematic Analysis Across Frontier Models
arXiv:2604. 19139v3 Announce Type: replace-cross Abstract: As Large Language Models (LLMs) continue to evolve through alignment techniques such as Reinforcement Learning from Human Feedback (RLHF) and Constitutional AI, a growing and increasingly conspicuous phenomenon has emerged: the proliferation of verbal tics--repetitive, formulaic linguistic patterns that pervade model outputs.
arXiv Machine Learning
3d ago
On the Monitorability of Natural Language Autoencoders: Identification vs Discrimination
arXiv:2610.18727v2 Announce Type: replace Abstract: Natural Language Autoencoders (NLAs) are proposed as oversight tools for language models: an Activation Verbaliser (AV) writes an English explanati...