Memory-R1: Enhancing Large Language Model Agents to Manage and Utilize Memories via Reinforcement Learning (2026 · 49 citations)
LLMs lose information that falls outside their context window. Systems that add an external memory bank usually depend on fixed heuristics or prompted LLMs to choose what to store and retrieve, and nothing in that choice is trained against answer correctness. Memory-R1 addresses this with reinforcement learning…
LLaVA Steering: Visual Instruction Tuning with 500x Fewer Parameters through Modality Linear Representation-Steering (2025 · 24 citations)
Multimodal LLMs built on the LLaVA recipe are expensive to adapt during visual instruction tuning, even with PEFT methods like LoRA.
Self-Evolving Multi-Agent Systems via Textual Backpropagation (2026 · 3 citations)
Building multi-agent LLM systems usually means hand-crafting prompts, roles and topologies by trial and error.

Co-authors here

11 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 55 times (of the 149,439 papers whose bibliographies we read); 20 citing papers with a page here →.

Updated 1 November 2026