Paper-Conference

Beyond Single-Task: Robust Multi-Task Length Generalization for LLMs
Length generalization, the ability to solve problems longer than those seen during training, remains a critical challenge for large …
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LooGLE v2: Are LLMs Ready for Real World Long Dependency Challenges?
LoRASuite: Efficient LoRA Adaptation Across Large Language Model Upgrades
As Large Language Models (LLMs) are frequently updated, LoRA weights trained on earlier versions quickly become obsolete. The …
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OCN: Effectively Utilizing Higher-Order Common Neighbors for Better Link Prediction
Common Neighbors (CNs) and their higher-order variants are important pairwise features widely used in state-of-the-art link prediction …
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PHYBench: Holistic Evaluation of Physical Perception and Reasoning in Large Language Models
Current benchmarks for evaluating the reasoning capabilities of Large Language Models (LLMs) face significant limitations: task …
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TransMLA: Migrating GQA Models to MLA with Full DeepSeek Compatibility and Speedup
In this paper, we present TransMLA, a framework that seamlessly converts any GQA-based pre-trained model into an MLA-based model. Our …
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Reconsidering the Performance of GAE in Link Prediction
Recent advancements in graph neural networks (GNNs) for link prediction have introduced sophisticated training techniques and model …
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CLOVER: Cross-Layer Orthogonal Vectors Pruning and Fine-Tuning
Decoder-only models generate tokens autoregressively by caching key/value vectors, but as the cache grows, inference becomes …
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Geometric Representation Condition Improves Equivariant Molecule Generation
Recent advances in molecular generative models have demonstrated great promise for accelerating scientific discovery, particularly in …
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Griffin: Towards a Graph-Centric Relational Database Foundation Model
We introduce Griffin, the first foundation model designed specifically for Relational Databases (RDBs). Unlike previous smaller models …
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