Academic
arXiv:2602.15896v1 Announce Type: new Abstract: Multi-modal knowledge graph reasoning (MMKGR) aims to predict the missing links by exploiting both graph structure information and multi-modal entity …
arXiv:2602.15897v1 Announce Type: new Abstract: Training and fine-tuning large-scale language models largely benefit from collaborative learning, but the approach has been proven vulnerable to gradient …
arXiv:2602.15898v1 Announce Type: new Abstract: Multi-hop question answering (QA) necessitates multi-step reasoning and retrieval across interconnected subjects, attributes, and relations. Existing retrieval-augmented generation (RAG) methods …
arXiv:2602.15958v1 Announce Type: new Abstract: Document understanding in real-world applications often requires processing heterogeneous, multi-page document packets containing multiple documents stitched together. Despite recent advances …
arXiv:2602.16023v1 Announce Type: new Abstract: Multiword expressions (MWEs) have been widely studied in cross-lingual annotation frameworks such as PARSEME. However, Korean MWEs remain underrepresented in …
arXiv:2602.16054v1 Announce Type: new Abstract: The prefill stage in long-context LLM inference remains a computational bottleneck. Recent token-ranking heuristics accelerate inference by selectively processing a …
arXiv:2602.16080v1 Announce Type: new Abstract: Where should we intervene in a language model (LM) to control behaviors that are diffused across many tokens of a …
arXiv:2602.16085v1 Announce Type: new Abstract: Research on mental state reasoning in language models (LMs) has the potential to inform theories of human social cognition--such as …
arXiv:2602.16093v1 Announce Type: new Abstract: Post-training endows pretrained LLMs with a variety of desirable skills, including instruction-following, reasoning, and others. However, these post-trained LLMs only …
arXiv:2602.16144v1 Announce Type: new Abstract: As multimodal systems increasingly process sensitive personal data, the ability to selectively revoke specific data modalities has become a critical …
arXiv:2602.16154v1 Announce Type: new Abstract: Chain-of-thought (CoT) reasoning sometimes fails to faithfully reflect the true computation of a large language model (LLM), hampering its utility …
arXiv:2602.16162v1 Announce Type: new Abstract: We argue that uncertainty is a key and understudied limitation of LLMs' performance in creative writing, which is often characterized …
