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Found 19 papers, 15 papers with code
"A good pun is its own reword": Can Large Language Models Understand Puns?
Puns play a vital role in academic research due to their distinct structure and clear definition, which aid in the comprehensive analysis of linguistic humor.
Evaluating Character Understanding of Large Language Models via Character Profiling from Fictional Works
These results strongly validate the character understanding capability of LLMs.
Character is Destiny: Can Large Language Models Simulate Persona-Driven Decisions in Role-Playing?
Can Large Language Models substitute humans in making important decisions?
TimeArena: Shaping Efficient Multitasking Language Agents in a Time-Aware Simulation
Despite remarkable advancements in emulating human-like behavior through Large Language Models (LLMs), current textual simulations do not adequately address the notion of time.
Unsupervised Generation of Pseudo Normal PET from MRI with Diffusion Model for Epileptic Focus Localization
In this study, we investigated unsupervised learning methods for unpaired MRI to PET translation for generating pseudo normal FDG PET for epileptic focus localization.
EASYTOOL: Enhancing LLM-based Agents with Concise Tool Instruction
EasyTool purifies essential information from extensive tool documentation of different sources, and elaborates a unified interface (i. e., tool instruction) to offer standardized tool descriptions and functionalities for LLM-based agents.
TaskBench: Benchmarking Large Language Models for Task Automation
To this end, we introduce TaskBench to evaluate the capability of LLMs in task automation.
InCharacter: Evaluating Personality Fidelity in Role-Playing Agents through Psychological Interviews
This paper, instead, introduces a novel perspective to evaluate the personality fidelity of RPAs with psychological scales.
Put Your Money Where Your Mouth Is: Evaluating Strategic Planning and Execution of LLM Agents in an Auction Arena
Recent advancements in Large Language Models (LLMs) showcase advanced reasoning, yet NLP evaluations often depend on static benchmarks.
Translate Meanings, Not Just Words: IdiomKB's Role in Optimizing Idiomatic Translation with Language Models
To translate well, machine translation (MT) systems and general-purposed language models (LMs) need a deep understanding of both source and target languages and cultures.
Beneath Surface Similarity: Large Language Models Make Reasonable Scientific Analogies after Structure Abduction
The vital role of analogical reasoning in human cognition allows us to grasp novel concepts by linking them with familiar ones through shared relational structures.
ANALOGYKB: Unlocking Analogical Reasoning of Language Models with A Million-scale Knowledge Base
Analogical reasoning is a fundamental cognitive ability of humans.
Distilling Script Knowledge from Large Language Models for Constrained Language Planning
In everyday life, humans often plan their actions by following step-by-step instructions in the form of goal-oriented scripts.
Causality-aware Concept Extraction based on Knowledge-guided Prompting
The prompt adopts the topic of the given entity from the existing knowledge in KGs to mitigate the spurious co-occurrence correlations between entities and biased concepts.
The Contribution of Human Body Capacitance/Body-Area Electric Field To Individual and Collaborative Activity Recognition
In the second case, we tried to recognize actions related to manipulating objects and physical collaboration between users by using a wrist-worn HBC sensing unit.
Generative Entity Typing with Curriculum Learning
To overcome these drawbacks, we propose a novel generative entity typing (GET) paradigm: given a text with an entity mention, the multiple types for the role that the entity plays in the text are generated with a pre-trained language model (PLM).
Large-scale Multi-granular Concept Extraction Based on Machine Reading Comprehension
In order to supply existing KGs with more fine-grained and new concepts, we propose a novel concept extraction framework, namely MRC-CE, to extract large-scale multi-granular concepts from the descriptive texts of entities.
Contextual Information and Commonsense Based Prompt for Emotion Recognition in Conversation
The newly proposed ERC models have leveraged pre-trained language models (PLMs) with the paradigm of pre-training and fine-tuning to obtain good performance.
Massive Twinning to Enhance Emergent Intelligence
As a complement to conventional AI solutions, emergent intelligence (EI) exhibits competitiveness in 6G IIoT scenario for its various outstanding features including robustness, protection to privacy, and scalability.
