Papers by Sihui Dai
ImReasoner: Improving Memory-based Language Models for Reasoning-in-a-Haystack Tasks (2026.acl-long)
Copied to clipboard
Ching-Yun Ko, Payel Das, Sihui Dai, Georgios Kollias, Subhajit Chaudhury, Aurelie C. Lozano, Pin-Yu Chen
| Challenge: | despite advances, large language models exhibit brittleness on tasks that require multi-step reasoning over long contexts. |
| Approach: | They propose to explicitly encode contexts as ordered memory and perform iterative retrieval to construct reasoning chains. |
| Outcome: | The proposed frameworks fail to show emergent reasoning generalization in a weakly supervised scenario . the proposed framework is based on a synthetic benchmark to stress-test the models . |