few-shot learning 1large multimodal models 1post-hoc correction 1visual species recognition 1zero-shot classification 1
From the 1 of 3 linked papers with an AI index.
3 papers
cs.LG2026
Visual Species Recognition with Large Multimodal Models as Post-Hoc Correctors
Tian Liu, Anwesha Basu, James Caverlee +1
The paper introduces a training-free post-hoc correction framework that uses large multimodal models to improve few-shot expert models for visual species recognition, boosting accu…
cs.CV2026
Solving Semi-Supervised Few-Shot Learning from an Auto-Annotation Perspective
Tian Liu, Anwesha Basu, James Caverlee +1
Semi-supervised few-shot learning (SSFSL) resembles real-world applications such as auto-annotation, as it aims to learn a model from a few labeled and abundant unlabeled task-spec…
cs.AI2025
Complex LLM Planning via Automated Heuristics Discovery
Hongyi Ling, Shubham Parashar, Sambhav Khurana +6
We consider enhancing large language models (LLMs) for complex planning tasks. While existing methods allow LLMs to explore intermediate steps to make plans, they either depend on…