4 citations · 5 across the 5 of their papers we have counts for
6 papers
The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning
Shivam Agarwal, Zimin Zhang, Lifan Yuan +2
Entropy minimization (EM) trains the model to concentrate even more probability mass on its most confident outputs. We show that this simple objective alone, without any labeled da…
Scaling Diffusion Language Models via Adaptation from Autoregressive Models
Shansan Gong, Shivam Agarwal, Yizhe Zhang +9
Diffusion Language Models (DLMs) have emerged as a promising new paradigm for text generative modeling, potentially addressing limitations of autoregressive (AR) models. However, c…
Improving Retrieval in Theme-specific Applications using a Corpus Topical Taxonomy
SeongKu Kang, Shivam Agarwal, Bowen Jin +3
Document retrieval has greatly benefited from the advancements of large-scale pre-trained language models (PLMs). However, their effectiveness is often limited in theme-specific ap…
Text-Augmented Open Knowledge Graph Completion via Pre-Trained Language Models
Pengcheng Jiang, Shivam Agarwal, Bowen Jin +3
The mission of open knowledge graph (KG) completion is to draw new findings from known facts. Existing works that augment KG completion require either (1) factual triples to enlarg…
Cryptocurrency Bubble Detection: A New Stock Market Dataset, Financial Task & Hyperbolic Models
Ramit Sawhney, Shivam Agarwal, Vivek Mittal +3
The rapid spread of information over social media influences quantitative trading and investments. The growing popularity of speculative trading of highly volatile assets such as c…
Deep Residual Neural Networks for Image in Speech Steganography
Shivam Agarwal, Siddarth Venkatraman
Steganography is the art of hiding a secret message inside a publicly visible carrier message. Ideally, it is done without modifying the carrier, and with minimal loss of informati…