2 citations · 2 across the 14 of their papers we have counts for
5 papers · 1 filter
On the SPOT: Enhancing Speculative Decoding for Diffusion Language Models via Commit-Order Prediction
Eliezer Shlomi, Eliron Rahimi, Avi Mendelson +1
Diffusion language models (DLMs) promise parallel text generation, but in practice face an unresolved speed-quality trade-off. Exact decoding fills in only one masked position per…
AnchorRep: Defending LLMs Against Cross-Model Adversarial Transfer via Representation Repulsion
Gal Wertheizer, Rom Himelstein, Tomer Peretz +1
Adversarial attacks optimized on a single open-weight LLM can transfer to and jailbreak architecturally different models, allowing an attacker with white-box access to one model to…
Breaking the Bubble: Asynchronous Pipeline Parallel Training with Bounded Weight Inconsistency
Itay Elam, Eliron Rahimi, Avi Mendelson +1
Pipeline parallelism is essential for training large neural networks, but existing schedules trade off throughput, memory, and optimization consistency. Synchronous pipelines prese…
Step-Wise Refusal Dynamics in Autoregressive and Diffusion Language Models
Eliron Rahimi, Elad Hirshel, Rom Himelstein +3
Diffusion language models (DLMs) have recently emerged as a competitive alternative to autoregressive (AR) models, offering parallel decoding, competitive generation quality, and i…
Hysteresis Activation Function for Efficient Inference
Moshe Kimhi, Idan Kashani, Avi Mendelson +1
The widely used ReLU is favored for its hardware efficiency, {as the implementation at inference is a one bit sign case,} yet suffers from issues such as the ``dying ReLU'' problem…