1 citations · 1 across the 4 of their papers we have counts for
5 papers
Fractional State Space Transition for Long Sequence Modeling
Ivan Kobyzev, Abbas Ghaddar, Ali Nasiri-Sarvi +2
State Space Models (SSMs) compress sequence history into a bounded recurrent state, making the resulting memory law a central architectural choice for long-context performance. Mos…
Survival-Guided Length Control for Efficient Diffusion Language Models
Ivan Kobyzev, Abbas Ghaddar, Yufei Cui
Diffusion language models (DLMs) generate text by iteratively denoising masked sequences, but standard decoding either fixes the sequence length or relies on ad hoc stopping rules,…
BOSCH: Black-Box Binary Optimization for Short-Context Attention-Head Selection in LLMs
Abbas Ghaddar, Ivan Kobyzev, Boxing Chen +1
Post-training hybridization of large language models (LLMs) often replaces quadratic self-attention with sliding-window attention (SWA) to reduce KV cache usage and improve latency…
Omni-Thinker: Scaling Multi-Task RL in LLMs with Hybrid Reward and Task Scheduling
Derek Li, Jiaming Zhou, Leo Maxime Brunswic +8
The pursuit of general-purpose artificial intelligence depends on large language models (LLMs) that can handle both structured reasoning and open-ended generation. We present Omni-…
Enhancing Logical Reasoning in Large Language Models through Graph-based Synthetic Data
Jiaming Zhou, Abbas Ghaddar, Ge Zhang +7
Despite recent advances in training and prompting strategies for Large Language Models (LLMs), these models continue to face challenges with complex logical reasoning tasks that in…