7 papers
ZoomR: Memory Efficient Reasoning through Multi-Granularity Key Value Retrieval
David H. Yang, Yuxuan Zhu, Mohammad Mohammadi Amiri +4
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…
Answering the Wrong Question: Reasoning Trace Inversion for Abstention in LLMs
Abinitha Gourabathina, Inkit Padhi, Manish Nagireddy +2
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 impre…
TabSketchFM: Sketch-based Tabular Representation Learning for Data Discovery over Data Lakes
Aamod Khatiwada, Harsha Kokel, Ibrahim Abdelaziz +7
Enterprises have a growing need to identify relevant tables in data lakes; e.g. tables that are unionable, joinable, or subsets of each other. Tabular neural models can be helpful…
LongFuncEval: Measuring the effectiveness of long context models for function calling
Kiran Kate, Tejaswini Pedapati, Kinjal Basu +5
Multiple recent studies have documented large language models' (LLMs) performance on calling external tools/functions. Others focused on LLMs' abilities to handle longer context le…
Can Memory-Augmented Language Models Generalize on Reasoning-in-a-Haystack Tasks?
Payel Das, Ching-Yun Ko, Sihui Dai +3
Large language models often expose their brittleness in reasoning tasks, especially while executing long chains of reasoning over context. We propose MemReasoner, a new and simple…
EpMAN: Episodic Memory AttentioN for Generalizing to Longer Contexts
Subhajit Chaudhury, Payel Das, Sarathkrishna Swaminathan +6
Recent advances in Large Language Models (LLMs) have yielded impressive successes on many language tasks. However, efficient processing of long contexts using LLMs remains a signif…