4 citations · 14 across the 32 of their papers we have counts for
3 papers · 2 filters
DISCO: Distributed Long Context Scaling with Grounding-Reasoning Disaggregation
Guanzheng Chen, Viet Dac Lai, Subhojyoti Mukherjee +5
While Large Language Models (LLMs) advertise million-token context windows, reasoning quality often collapses as inputs grow -- a phenomenon termed context rot. This failure stems…
Bridging the Reasoning Gap in Vietnamese with Small Language Models via Test-Time Scaling
Bui The Trung, Do Minh Duc, Nguyen Van Vinh +1
The democratization of ubiquitous AI hinges on deploying sophisticated reasoning capabilities on resource-constrained devices. However, Small Language Models (SLMs) often face a "r…
Can Large Language Models Keep Up? Benchmarking Online Adaptation to Continual Knowledge Streams
Jiyeon Kim, Hyunji Lee, Dylan Zhou +6
LLMs operating in dynamic real-world contexts often encounter knowledge that evolves continuously or emerges incrementally. To remain accurate and effective, models must adapt to n…