BABILong: Testing the Limits of LLMs with Long Context Reasoning-in-a-Haystack (2024 · 88 citations)
Context windows of LLMs now reach hundreds of thousands or millions of tokens. Yet common evaluations either stop around 40K tokens (Longbench, L-Eval) or use needle-in-a-haystack retrieval, which strong models already solve perfectly. BABILong fills this gap with the 20 synthetic bAbI reasoning tasks, which cover…
Associative Recurrent Memory Transformer (2024 · 8 citations)
The authors address a core difficulty in long-context modeling: building a network whose cost for each new chunk of input stays fixed, however long the sequence grows.
Beyond Memorization: Extending Reasoning Depth with Recurrence, Memory and Test-Time Compute Scaling (2026)
The paper asks whether multi-step reasoning in neural models reflects real generalization or memorization, and how difficulty grows with the number of required inference steps.

Co-authors here

9 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

Papers of our library cite their works 80 times (of the 149,439 papers whose bibliographies we read); 19 citing papers with a page here →.

Updated 2 November 2026