Papers by Hamidreza Saghir
A Cross-Domain Transferable Neural Coherence Model (P19-1)
Copied to clipboard
Peng Xu, Hamidreza Saghir, Jin Sung Kang, Teng Long, Avishek Joey Bose, Yanshuai Cao, Jackie Chi Kit Cheung
| Challenge: | Existing coherence models do not generalize to unseen categories of text . previous work advocates for generative models for cross-domain generalization . |
| Approach: | They propose a local discriminative neural model with a smaller negative sampling space that can discriminate against incorrect orderings. |
| Outcome: | The proposed model outperforms state-of-the-art methods on a standard benchmark dataset on the Wall Street Journal corpus and multiple challenging settings on Wikipedia articles. |
Llama See, Llama Do: A Mechanistic Perspective on Contextual Entrainment and Distraction in LLMs (2025.acl-long)
Copied to clipboard
| Challenge: | *contextual entrainment* occurs across a wide range of language models (LMs) and prompt settings. |
| Approach: | They hypothesize that there is a circuit of attention heads that corresponds to the phenomenon *contextual entrainment* . when they "turn off" these heads, the effect of contextual entraining is significantly attenuated. |
| Outcome: | The proposed method shows that LMs assign higher logits to tokens that have previously appeared in the context prompt, even for random tokens. |