arXiv Machine Learning
Jul 21
The Anatomy of a Truth Direction: Knowledge-Dependent Dimensionality, a Relational Law, and a Convergent Category Geometry in Small Language Models
arXiv:2607. 16741v1 Announce Type: new Abstract: B\"urger et al.
How Context Shapes Truth: Geometric Transformations of Statement-level Truth Representations in LLMs
arXiv:2601. 06599v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) often encode whether a statement is true as a vector in their residual stream activations.
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arXiv AI
Jun 16
The Truth Stays in the Family: Enhancing Contextual Grounding via Inherited Truthful Heads in Model Lineages
arXiv:2606. 15821v1 Announce Type: cross Abstract: Recent advances in large language models (LLMs) have produced many specialized multimodal LLMs (MLLMs) that share common foundational LLMs, forming distinct model lineages.
arXiv Machine Learning
Aug 10
Latent Fact-Checking: Detecting Misinformation through Activation Engineering
arXiv:2608. 06417v1 Announce Type: new Abstract: The proliferation of misinformation online has driven demand for scalable detection systems.
arXiv AI
Jun 3
Hallucinations as Orthogonal Noise: Inference-Time Manifold Alignment via Dynamic Contextual Orthogonalization
arXiv:2606. 03022v1 Announce Type: cross Abstract: Hallucination in Large Language Models (LLMs), characterized by the generation of content inconsistent with contextual facts or logical constraints -- remains a persistent challenge for reliable deployment.
arXiv Machine Learning
22h ago
FishBack: Pullback Fisher Geometry for Optimal Activation Steering in Transformers
arXiv:2605. 17231v2 Announce Type: replace Abstract: Activation steering has emerged as a lightweight approach for modifying language model behavior without parameter updates, yet existing methods remain brittle: unstable across layers and prone to disturbing behavior unrelated to the target concept.
arXiv Machine Learning
Aug 5
Inverted Detection and Control in Steering Vectors
arXiv:2608. 02957v1 Announce Type: new Abstract: Steering vectors (SVs) are widely used to influence the expression of concepts (e.
arXiv Machine Learning
Jun 25
Evidence for feature-specific error correction in LLMs
arXiv:2606. 24964v1 Announce Type: new Abstract: Understanding the features of large language models (LLMs) is a central goal of interpretability.
Hugging Face Trending Papers
Jul 27
Context Is King: How In-Context Specification Shapes the Geometry of Concepts
Large language models place structured concepts on geometrically faithful manifolds: weekdays lie on a circle, months on another, usually taken to be a fixed world-model the network stores and looks up. We show that context is king: the structure a model actually uses is set by the in-context specification.
arXiv Machine Learning
Jul 31
The Confidence Manifold: Geometric Structure of Correctness Representations in Language Models
arXiv:2602. 08159v2 Announce Type: replace Abstract: When a language model asserts that "the capital of Australia is Sydney," does it know this is wrong?
arXiv Machine Learning
Jul 28
Context Is King: How In-Context Specification Shapes the Geometry of Concepts
arXiv:2607. 24425v1 Announce Type: new Abstract: Large language models place structured concepts on geometrically faithful manifolds: weekdays lie on a circle, months on another, usually taken to be a fixed world-model the network stores and looks up.
arXiv AI
Jul 7
Language Models Represent and Transform Concepts with Shared Geometry
arXiv:2607. 04525v1 Announce Type: cross Abstract: How concepts are represented in neural networks is a fundamental question in machine learning.
arXiv AI
Jul 14
Laguerre Geometry for Interpreting Large Language Models
arXiv:2607. 10578v1 Announce Type: new Abstract: Existing hypotheses represent a concept in an LLM as a single point, a linear direction, or a Gaussian cluster, yet it remains unclear how and why such structures emerge.