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Yue Huang · Hang Hua · Yujun Zhou · Pengcheng Jing · Manish Nagireddy · Inkit Padhi · Greta Dolcetti · Zhangchen Xu · Subhajit Chaudhury · Ambrish Rawat · Liubov Nedoshivina · Pin-Yu Chen · Prasanna Sattigeri · Xiangliang Zhang
Ching-Yun Ko · Payel Das · Sihui Dai · Georgios Kollias · Subhajit Chaudhury · Aurelie C. Lozano · Pin-Yu Chen
Reasoning over long contexts remains a major challenge for language models, particularly when solving tasks that require integrating multiple facts in sequence or generalizing to new distributions. We argue that this difficulty stems from a lack of structural inductive bias. Recently, alternative...
David H. Yang · Yuxuan Zhu · Mohammad Mohammadi Amiri · Keerthiram Murugesan · Tejaswini Pedapati · Subhajit Chaudhury · Pin-Yu Chen
Large language models (LLMs) have shown great performance on complex reasoning tasks but often require generating long intermediate thoughts before reaching a final answer. During generation, LLMs rely on a key-value (KV) cache for autoregressive decoding. However, the memory footprint of the KV...
Abinitha Gourabathina · Inkit Padhi · Manish Nagireddy · Subhajit Chaudhury · Prasanna Sattigeri
For Large Language Models (LLMs) to be reliably deployed, models must effectively know when not to answer: abstain. Reasoning models, in particular, have gained attention for impressive performance on complex tasks. However, reasoning models have been shown to have worse abstention abilities. Tak...