2 citations · 4 across the 13 of their papers we have counts for
4 papers · 1 filter
Can Language Model Agents be Helpful Circuit Explainers in Mechanistic Interpretability?
Ayan Antik Khan, Harsh Kohli, Yuekun Yao +2
Mechanistic interpretability has made substantial progress in automatically localizing circuits, but explaining what localized components do remains labor-intensive and difficult t…
QUEST: Training Frontier Deep Research Agents with Fully Synthetic Tasks
Jian Xie, Tianhe Lin, Zilu Wang +16
Deep research agents extend the role of search engines from retrieving keyword-matched pages to synthesizing knowledge, fundamentally changing how humans interact with information.…
Barriers to Universal Reasoning With Transformers (And How to Overcome Them)
Oliver Kraus, Yash Sarrof, Yuekun Yao +2
Chain-of-Thought (CoT) has been shown to empirically improve Transformers' performance, and theoretically increase their expressivity to Turing completeness. However, whether Trans…
Loop, Think, & Generalize: Implicit Reasoning in Recurrent-Depth Transformers
Harsh Kohli, Srinivasan Parthasarathy, Huan Sun +1
We study implicit reasoning, i.e. the ability to combine knowledge or rules within a single forward pass. While transformer-based large language models store substantial factual kn…