21 citations · 33 across the 8 of their papers we have counts for
12 papers · 1 filter
Weight Tying Biases Token Embeddings Towards the Output Space
Antonio Lopardo, Avyukth Harish, Catherine Arnett +1
Weight tying, i.e. sharing parameters between input and output embedding matrices, is common practice in language model design, yet its impact on the learned embedding space remain…
PokerBench: Training Large Language Models to become Professional Poker Players
Richard Zhuang, Akshat Gupta, Richard Yang +3
We introduce PokerBench - a benchmark for evaluating the poker-playing abilities of large language models (LLMs). As LLMs excel in traditional NLP tasks, their application to compl…
Sylber: Syllabic Embedding Representation of Speech from Raw Audio
Cheol Jun Cho, Nicholas Lee, Akshat Gupta +4
Syllables are compositional units of spoken language that efficiently structure human speech perception and production. However, current neural speech representations lack such str…
FineZip : Pushing the Limits of Large Language Models for Practical Lossless Text Compression
Fazal Mittu, Yihuan Bu, Akshat Gupta +4
While the language modeling objective has been shown to be deeply connected with compression, it is surprising that modern LLMs are not employed in practical text compression syste…
Is Bigger Edit Batch Size Always Better? -- An Empirical Study on Model Editing with Llama-3
Junsang Yoon, Akshat Gupta, Gopala Anumanchipalli
This study presents a targeted model editing analysis focused on the latest large language model, Llama-3. We explore the efficacy of popular model editing techniques - ROME, MEMIT…
On Building Spoken Language Understanding Systems for Low Resourced Languages
Akshat Gupta
Spoken dialog systems are slowly becoming and integral part of the human experience due to their various advantages over textual interfaces. Spoken language understanding (SLU) sys…