3 papers
cs.LG2026
Efficient Reasoning on the Edge
Yelysei Bondarenko, Thomas Hehn, Rob Hesselink +15
Large language models (LLMs) with chain-of-thought reasoning achieve state-of-the-art performance across complex problem-solving tasks, but their verbose reasoning traces and large…
cs.AI2026
LaneRoPE: Positional Encoding for Collaborative Parallel Reasoning and Generation
Gabriele Cesa, Thomas Hehn, Aleix Torres-Camps +4
Parallel LLM test-time scaling techniques (e.g., best-of-) require drawing sequences conditioned on the same input prompt. These methods boost accuracy while exploiting th…
cs.AI2026
LUMINA: Long-horizon Understanding for Multi-turn Interactive Agents
Amin Rakhsha, Thomas Hehn, Pietro Mazzaglia +3
Large language models can perform well on many isolated tasks, yet they continue to struggle on multi-turn, long-horizon agentic problems that require skills such as planning, stat…