AI
Recalling Too Well: Sycophancy Evaluation and Mitigation in Memory-Augmented Models
Researchers have found that memory-augmented language models can become overly agreeable and less ac...
AI
Relational Structural Causal Models
Researchers have proposed a new type of model called Relational Structural Causal Models (RSCMs) to ...
AI
Incumbent Advantage: Brand Bias and Cognitive Manipulation Dynamics in LLM Recommendation Systems
Researchers have found that large language models (LLMs) used for product recommendations often favo...
AI
FinAcumen: Financial Multimodal Reasoning via Self-Evolving Experience Memory Harness
Researchers have developed FinAcumen, a framework for financial multimodal reasoning that uses selec...
AI
DiagFlowBench: Evaluating How Language Models Handle Off-Procedure Inputs in Grounded Diagnostic Dialogue
Researchers have created DiagFlowBench, a dataset designed to test how language ...
AI
MoCo-AIS: A Contrastive Learning Framework for Similarity Computation of Vessel Trajectories
Researchers have developed MoCo-AIS, a framework for computing similarity betwee...
AI
Lagrange: An Open-Vocabulary, Energy-Based Sparse Framework for Generalized End-to-End Driving
Researchers have proposed an open-vocabulary, energy-based sparse framework call...
AI
Scaling Laws for Task-Specific LLM Distillation
Researchers have developed empirical scaling laws for compressing large language...