2 citations · 2 across the 15 of their papers we have counts for
6 papers · 1 filter
Teaching and Evaluating LLMs to Reason About Polymer Design Related Tasks
Dikshya Mohanty, Mohammad Saqib Hasan, Syed Mostofa Monsur +3
Research in AI4Science has shown promise in many science applications, including polymer design. However, current LLMs are ineffective in this problem space because: (i) most model…
ProST: Progressive Sub-task Training for Pareto-Optimal Multi-agent Systems Using Small Language Models
Biddut Sarker Bijoy, Mohammad Saqib Hasan, Pegah Alipoormolabashi +3
Multi-agent systems with smaller language models (SLMs) present a viable alternative to single agent systems powered by large language models (LLMs) for addressing complex problems…
MuSciClaims: Multimodal Scientific Claim Verification
Yash Kumar Lal, Manikanta Bandham, Mohammad Saqib Hasan +3
Assessing scientific claims requires identifying, extracting, and reasoning with multimodal data expressed in information-rich figures in scientific literature. Despite the large b…
Quantifying Misattribution Unfairness in Authorship Attribution
Pegah Alipoormolabashi, Ajay Patel, Niranjan Balasubramanian
Authorship misattribution can have profound consequences in real life. In forensic settings simply being considered as one of the potential authors of an evidential piece of text o…
On Initializing Transformers with Pre-trained Embeddings
Ha Young Kim, Niranjan Balasubramanian, Byungkon Kang
It has become common practice now to use random initialization schemes, rather than the pre-trained embeddings, when training transformer based models from scratch. Indeed, we find…
CaT-BENCH: Benchmarking Language Model Understanding of Causal and Temporal Dependencies in Plans
Yash Kumar Lal, Vanya Cohen, Nathanael Chambers +2
Understanding the abilities of LLMs to reason about natural language plans, such as instructional text and recipes, is critical to reliably using them in decision-making systems. A…