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Found 13 papers, 10 papers with code
Advancing Geometric Problem Solving: A Comprehensive Benchmark for Multimodal Model Evaluation
In this work, we present the MM-MATH dataset, a novel benchmark developed to rigorously evaluate the performance of advanced large language and multimodal models - including but not limited to GPT-4, GPT-4V, and Claude - within the domain of geometric computation.
CogCoM: Train Large Vision-Language Models Diving into Details through Chain of Manipulations
Vision-Language Models (VLMs) have demonstrated their widespread viability thanks to extensive training in aligning visual instructions to answers.
LongAlign: A Recipe for Long Context Alignment of Large Language Models
Extending large language models to effectively handle long contexts requires instruction fine-tuning on input sequences of similar length.
Text-Image Conditioned Diffusion for Consistent Text-to-3D Generation
By lifting the pre-trained 2D diffusion models into Neural Radiance Fields (NeRFs), text-to-3D generation methods have made great progress.
WaterBench: Towards Holistic Evaluation of Watermarks for Large Language Models
To mitigate the potential misuse of large language models (LLMs), recent research has developed watermarking algorithms, which restrict the generation process to leave an invisible trace for watermark detection.
Know2BIO: A Comprehensive Dual-View Benchmark for Evolving Biomedical Knowledge Graphs
Knowledge graphs (KGs) have emerged as a powerful framework for representing and integrating complex biomedical information.
T$^3$Bench: Benchmarking Current Progress in Text-to-3D Generation
Recent methods in text-to-3D leverage powerful pretrained diffusion models to optimize NeRF.
Large Language Models Can Be Good Privacy Protection Learners
To address this challenge, we introduce Privacy Protection Language Models (PPLM), a novel paradigm for fine-tuning LLMs that effectively injects domain-specific knowledge while safeguarding data privacy.
LongBench: A Bilingual, Multitask Benchmark for Long Context Understanding
In this paper, we introduce LongBench, the first bilingual, multi-task benchmark for long context understanding, enabling a more rigorous evaluation of long context understanding.
KoLA: Carefully Benchmarking World Knowledge of Large Language Models
The unprecedented performance of large language models (LLMs) necessitates improvements in evaluations.
Answering Complex Logical Queries on Knowledge Graphs via Query Computation Tree Optimization
QTO finds the optimal solution by a forward-backward propagation on the tree-like computation graph, i. e., query computation tree.
Ranked #1 on
Complex Query Answering
on NELL-995
SQUIRE: A Sequence-to-sequence Framework for Multi-hop Knowledge Graph Reasoning
Multi-hop knowledge graph (KG) reasoning has been widely studied in recent years to provide interpretable predictions on missing links with evidential paths.
Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Cones
Here we present ConE (Cone Embedding), a KG embedding model that is able to simultaneously model multiple hierarchical as well as non-hierarchical relations in a knowledge graph.
Ranked #1 on
Ancestor-descendant prediction
on WN18RR
Ancestor-descendant prediction
Knowledge Graph Completion
+2
