LLMs display prompt-sensitive risk behavior and a linearly decodable realization-status signal in Gemma's residual stream, yet activation steering along this direction fails to shift downstream risk choices.
The butterfly effect of altering prompts: How small changes and jailbreaks affect large language model performance.arXiv preprint arXiv:2401.03729
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Clinical VLMs over-rely on text modality, irrelevant clinical history, and prompt wording when making chest x-ray decisions on MIMIC-CXR data.
Prototype-Based Sparse Steering decomposes query activations with SAEs and optimizes sparse features via gradients to steer LLM outputs toward specific behaviors.
A survey proposing a three-pillar framework to evaluate LLMs as tools for measuring latent psychological constructs and reviewing applications in personality and mental health.
Advanced language representations shape LLMs' schemas to improve knowledge activation and problem-solving.
citing papers explorer
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Representation Without Control: Testing the Realization Effect in Language Models
LLMs display prompt-sensitive risk behavior and a linearly decodable realization-status signal in Gemma's residual stream, yet activation steering along this direction fails to shift downstream risk choices.
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Medical Context Distorts Decisions in Clinical Vision Language Models
Clinical VLMs over-rely on text modality, irrelevant clinical history, and prompt wording when making chest x-ray decisions on MIMIC-CXR data.
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Steered Generation via Gradient-Based Optimization on Sparse Query Features
Prototype-Based Sparse Steering decomposes query activations with SAEs and optimizes sparse features via gradients to steer LLM outputs toward specific behaviors.
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A Survey of Large Language Models for Perception and Measurement of Human Psychology
A survey proposing a three-pillar framework to evaluate LLMs as tools for measuring latent psychological constructs and reviewing applications in personality and mental health.
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Shaping Schema via Language Representation as the Next Frontier for LLM Intelligence Expanding
Advanced language representations shape LLMs' schemas to improve knowledge activation and problem-solving.