51 papers
When Does On-Policy Interaction Help? Representational Tradeoffs in Value-Based Imitation Learning
Luca Viano, Antoine Moulin, Audrey Huang +3
Imitation learning (IL)---training an agent to replicate expert behavior from demonstrations---underpins applications from robotics to language model training. Standard approaches…
Raven: High-Recall Sequence Modeling with Sparse Memory Routing
Arshia Afzal, Aviv Bick, Eric P. Xing +2
Raven is a linear-time sequence model that uses learned, input-dependent routing to update only a subset of fixed memory slots, reducing interference and improving long-range recal…
Attention-Discounted Adaptive Sampler for Masked Diffusion Language Models
Yusuf Sahin, Ahmed Rockey Saikia, Volkan Cevher +1
The paper proposes ADAS, a training‑free attention‑discounted reranking rule that improves parallel masked diffusion decoding by penalizing tokens that strongly attend to uncertain…
Multi-agent imitation learning with function approximation: Linear Markov games and beyond
Luca Viano, Till Freihaut, Emanuele Nevali +3
In this work, we present the first theoretical analysis of multi-agent imitation learning (MAIL) in linear Markov games where both the transition dynamics and each agent's reward f…
Selective Rotary Position Embedding
Sajad Movahedi, Timur Carstensen, Arshia Afzal +3
Position information is essential for language modeling. In softmax transformers, Rotary Position Embeddings (\textit{RoPE}) encode positions through \textit{fixed-angle} rotations…
Demystifying Variance in Circuit Discovery of LLMs
Frank Zhengqing Wu, Francesco Tonin, Volkan Cevher
Circuit discovery is a key technique in mechanistic interpretability to pinpoint the model components that are crucial for performing a given task. Although the current state-of-th…