3 accepted papers
Deep reinforcement learning-based Multi-Agent Path Finding (MAPF) has gained significant attention due to its remarkable adaptability to environments. Existing methods primarily leverage multi-agent communication in a fully-decentralized framework to maintain scalability while enhancing information
Large language models (LLMs) often struggle with processing extensive input contexts, which can lead to redundant, inaccurate, or incoherent summaries. Recent methods have used unstructured memory to incrementally process these contexts, but they still suffer from information overload due to the vol…
Building automatic extraction models for visually rich documents like invoices, receipts, bills, tax forms, etc. has received significant attention lately. A key bottleneck in developing extraction models for new document types is the cost of acquiring the several thousand high-quality labeled docum…