5 papers
Imbuing Large Language Models with Bidirectional Logic for Robust Chain Repair
Zehua Cheng, Wei Dai, Jiahao Sun +1
Autoregressive chain-of-thought (CoT) reasoning in large language models (LLMs) is fundamentally forward-directed: each step conditions only on prior tokens. This unidirectional in…
CasualSynth: Generating Structurally Sound Synthetic Data
Zehua Cheng, Wei Dai, Jiahao Sun +1
Large Language Models (LLMs) generate realistic synthetic data but offer no guarantee that their outputs respect the causal mechanisms governing the target domain. We introduce Cau…
CircuitSynth: Reliable Synthetic Data Generation
Zehua Cheng, Wei Dai, Jiahao Sun +1
The generation of high-fidelity synthetic data is a cornerstone of modern machine learning, yet Large Language Models (LLMs) frequently suffer from hallucinations, logical inconsis…
Visual Set Program Synthesizer
Zehua Cheng, Wei Dai, Wenhu Zhang +2
A user pointing their phone at a supermarket shelf and asking "Which soda has the least sugar?" poses a difficult challenge for current visual Al assistants. Such queries require n…
Detection-Fusion for Knowledge Graph Extraction from Videos
Taniya Das, Louis Mahon, Thomas Lukasiewicz
One of the challenging tasks in the field of video understanding is extracting semantic content from video inputs. Most existing systems use language models to describe videos in n…