The study focuses on improving the performance of large language models (LLMs) in tasks that involve repetitive sub-tasks or deceptive contents. Existing prompting strategies often fall short in these areas…
Continue readingThis academic article is a thorough review of over 300 articles that focus on the use of Knowledge Graphs (KGs) in Multi-modal Learning. It discusses two main aspects: KG-driven Multi-Modal…
Continue readingThis paper introduces RIPPLE, an optimization-based method that exploits subconsciousness and echopraxia to jailbreak Large Language Models (LLMs). LLMs, due to their extraordinary reasoning and comprehension abilities, are used widely…
Continue readingThis research paper presents R3, a novel method for training large language models (LLMs) in complex reasoning tasks. R3 uses reverse curriculum reinforcement learning (RL), which provides the benefits of…
Continue readingThis research paper investigates the negotiation abilities of Large Language Models (LLMs). The authors developed a flexible framework, NEGOTIATION ARENA, to evaluate and probe the LLMs’ negotiation skills. The ARENA…
Continue readingThe article discusses a new graph knowledge distillation framework, named LinguGKD, using Large Language Models (LLMs) as teacher models and Graph Neural Networks (GNNs) as student models for knowledge distillation….
Continue readingThe study presents aLLM4TS, an innovative framework that adapts Large Language Models (LLMs) for time-series representation learning. The approach reimagines time-series forecasting as a self-supervised, multi-patch prediction task, capturing temporal…
Continue readingThis article introduces L4Q, a novel algorithm for parameter-efficient quantization-aware training on Large Language Models (LLMs). L4Q aims to improve the generality of these models using a low-rank adaptation (LoRA)…
Continue readingThe study focuses on the role of Large Language Models (LLMs) in accelerating Bayesian optimization in molecular space. It emphasizes the importance of automation in material discovery, with Bayesian optimization…
Continue readingThis research presents Hydragen, a hardware-aware model that improves the efficiency of transformer-based large language models (LLMs) working with shared prefixes. It is common for LLMs to perform inferences on…
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