8 papers
SALT: Steering Activations towards Leakage-free Thinking in Chain of Thought
Shourya Batra, Pierce Tillman, Samarth Gaggar +6
As Large Language Models (LLMs) evolve into personal assistants with access to sensitive user data, they face a critical privacy challenge: while prior work has addressed output-le…
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…
Optimizing Chain-of-Thought Confidence via Topological and Dirichlet Risk Analysis
Abhishek More, Anthony Zhang, Nicole Bonilla +4
Chain-of-thought (CoT) prompting enables Large Language Models to solve complex problems, but deploying these models safely requires reliable confidence estimates, a capability whe…
PALADIN: Self-Correcting Language Model Agents to Cure Tool-Failure Cases
Sri Vatsa Vuddanti, Aarav Shah, Satwik Kumar Chittiprolu +4
Tool-augmented language agents frequently fail in real-world deployment due to tool malfunctions--timeouts, API exceptions, or inconsistent outputs--triggering cascading reasoning…
FRIT: Using Causal Importance to Improve Chain-of-Thought Faithfulness
Anand Swaroop, Akshat Nallani, Saksham Uboweja +7
Chain-of-thought (CoT) reasoning has emerged as a powerful tool for improving large language model performance on complex tasks, but recent work shows that reasoning steps often fa…
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 …