9 papers
From Personas to Plot: Character-Grounded Multi-Agent Story Generation for Long-Form Narratives
Aayush Aluru, Chloe Ho, Muhammad Hammouri +5
Although large language models (LLMs) have demonstrated impressive creative fiction generation, they struggle to maintain narrative consistency and coherent plot lines in long-form…
Mitigating Forgetting in Continual Learning with Selective Gradient Projection
Anika Singh, Aayush Dhaulakhandi, Varun Chopade +3
As neural networks are increasingly deployed in dynamic environments, they face the challenge of catastrophic forgetting, the tendency to overwrite previously learned knowledge whe…
CIPHER: Cryptographic Insecurity Profiling via Hybrid Evaluation of Responses
Max Manolov, Tony Gao, Siddharth Shukla +2
Large language models (LLMs) are increasingly used to assist developers with code, yet their implementations of cryptographic functionality often contain exploitable flaws. Minor d…
A Few Bad Neurons: Isolating and Surgically Correcting Sycophancy
Claire O'Brien, Jessica Seto, Dristi Roy +6
Behavioral alignment in large language models (LLMs) is often achieved through broad fine-tuning, which can result in undesired side effects like distributional shift and low inter…
Chopping Trees: Semantic Similarity Based Dynamic Pruning for Tree-of-Thought Reasoning
Joongho Kim, Xirui Huang, Zarreen Reza +1
Tree-of-Thought (ToT) reasoning boosts the problem-solving abilities of Large Language Models (LLMs) but is computationally expensive due to semantic redundancy, where distinct bra…
Alignment-Constrained Dynamic Pruning for LLMs: Identifying and Preserving Alignment-Critical Circuits
Dev Patel, Gabrielle Gervacio, Diekola Raimi +5
Large Language Models require substantial computational resources for inference, posing deployment challenges. While dynamic pruning offers superior efficiency over static methods…