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20242026
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cs.LG2026

Why DDIM Hallucinates More Than DDPM: A Theoretical Analysis of Reverse Dynamics

Muhammad H. Ashiq, Samanyu Arora, Abhinav N. Harish +3

We theoretically study the hallucination phenomena in two canonical diffusion samplers: the stochastic Denoising Diffusion Probabilistic Model (DDPM) and the deterministic Denoisin…

cs.LG2026

LJ-Bench: Ontology-Based Benchmark for U.S. Crime

Hung Yun Tseng, Wuzhen Li, Blerina Gkotse +1

The potential of Large Language Models (LLMs) to provide harmful information remains a significant concern due to the vast breadth of illegal queries they may encounter. Unfortunat…

cs.LG2026

Corrective Diffusion Language Models

Shuibai Zhang, Fred Zhangzhi Peng, Yiheng Zhang +2

While Diffusion Language Models (DLMs) are theoretically well-suited for iterative refinement due to their non-causal structure, they often fail to reliably revise incorrect tokens…

cs.LG2026

Towards Interpretability Without Sacrifice: Faithful Dense Layer Decomposition with Mixture of Decoders

James Oldfield, Shawn Im, Sharon Li +3

Multilayer perceptrons (MLPs) are an integral part of large language models, yet their dense representations render them difficult to understand, edit, and steer. Recent methods le…

cs.LG2025

Hadamard product in deep learning: Introduction, Advances and Challenges

Grigorios G Chrysos, Yongtao Wu, Razvan Pascanu +2

While convolution and self-attention mechanisms have dominated architectural design in deep learning, this survey examines a fundamental yet understudied primitive: the Hadamard pr…

cs.LG2025

Single-pass Detection of Jailbreaking Input in Large Language Models

Leyla Naz Candogan, Yongtao Wu, Elias Abad Rocamora +2

Defending aligned Large Language Models (LLMs) against jailbreaking attacks is a challenging problem, with existing approaches requiring multiple requests or even queries to auxili…