Back to feed
AI in TecharXiv cs.LG · June 29, 2026 · 4w ago

The Curse of Multiple Mediators: Hidden Interaction Effects in Activation Patching

arXiv:2606.27510v1 Announce Type: new Abstract: Activation patching is the primary tool in mechanistic interpretability. It attributes causal responsibility for a model behavior to each of its individual components by estimating its natural indirect effect (NIE). Re-deriving the activation patching estimand from causal mediation analysis, we find that the NIE does not solely capture the causal effect through the specific component. It also contains interaction effects (INT) that measure how much

Open original

The Daily Drop

Join 1,000+ people who read this first.

Related stories

Generating in the Limit with Infinitely Many Hallucinations

arXiv:2606.28354v1 Announce Type: new Abstract: The classic paradigm of language identification in the limit models learning as a game between an adversary, who reveals strings from an unknown target language, and a learner tasked with identifying that language. The recently introduced framework of language generation in the limit shifted the objective to better reflect modern language modeling, requiring the learner to produce valid, unseen strings from the target language. Related work highlig

arXiv cs.CL · 4w ago

Extracting Knowledge from an Arabic-English Machine-Readable Dictionary Using Information Extraction

arXiv:2606.28457v1 Announce Type: new Abstract: Natural language processing (NLP) applications need large and rich amount of linguistic knowledge. Furthermore, electronic language sources such as dictionaries, encyclopedia, and corpora became available. So, automatic methods are emerged to extract lexical information from those sources to overcome the knowledge acquisition bottleneck. We presented a method to automatically extract lexical information from a machine-readable version of the Arabic

arXiv cs.CL · 4w ago

Developmental Trajectories of Situation Modeling and Mentalizing in Transformer Language Models

arXiv:2606.28524v1 Announce Type: new Abstract: Recent work suggests that Large Language Models (LLMs) are sensitive to the belief states of agents described by text, as measured by the false belief task (FBT), yet persistent concerns of construct validity remain. We adopt a **developmental perspective**, tracing the pattern of mental state reasoning behavior -- and likely **preconditions** for this behavior -- across multiple training stages in the Olmo2 and Pythia language model suites. We fin

arXiv cs.CL · 4w ago