8 papers · 1 filter
Broken Chains: The Cost of Incomplete Reasoning in LLMs
Ian Su, Gaurav Purushothaman, Jey Narayan +5
Reasoning-specialized models like OpenAI's 5.1 and DeepSeek-V3.2 allocate substantial inference compute to extended chain-of-thought (CoT) traces, yet reasoning tokens incur signif…
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…
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…
Peek-a-Boo Reasoning: Contrastive Region Masking in MLLMs
Isha Chaturvedi, Anjana Nair, Yushen Li +5
We introduce Contrastive Region Masking (CRM), a training free diagnostic that reveals how multimodal large language models (MLLMs) depend on specific visual regions at each step o…
Sumudu Neural Operator for ODEs and PDEs
Ben Zelenskiy, Saibilila Abudukelimu, George Flint +2
We introduce the Sumudu Neural Operator (SNO), a neural operator rooted in the properties of the Sumudu Transform. We leverage the relationship between the polynomial expansions of…
Amortized Latent Steering: Low-Cost Alternative to Test-Time Optimization
Nathan Egbuna, Saatvik Gaur, Sunishchal Dev +2
Test-time optimization remains impractical at scale due to prohibitive inference costs--techniques like iterative refinement and multi-step verification can require …