3 accepted papers
Long-context models are essential for many applications but face inefficiencies in loading large KV caches during decoding. Prior methods enforce fixed token budgets for sparse attention, assuming a set number of tokens can approximate full attention. However, these methods overlook variations in th…
The ability to model interactions among agents is crucial for effective coordination and understanding their cooperation mechanisms in multi-agent reinforcement learning (MARL). However, previous efforts to model high-order interactions have been primarily hindered by the combinatorial explosion or…
This paper presents an Open-Structure Table Extraction (OpenTE) task, which aims to extract a table with intrinsic semantic, calculational, and hierarchical structure from unstructured text. We devise a novel Identification-Extraction-Grounding (IEG) framework for language models (LMs) comprising th…