Search Results for author:
Found 28 papers, 19 papers with code
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?
SurveyAgent: A Conversational System for Personalized and Efficient Research Survey
In the rapidly advancing research fields such as AI, managing and staying abreast of the latest scientific literature has become a significant challenge for researchers.
How Easily do Irrelevant Inputs Skew the Responses of Large Language Models?
By leveraging the retrieval of information from external knowledge databases, Large Language Models (LLMs) exhibit enhanced capabilities for accomplishing many knowledge-intensive tasks.
AgentGroupChat: An Interactive Group Chat Simulacra For Better Eliciting Emergent Behavior
Language significantly influences the formation and evolution of Human emergent behavior, which is crucial in understanding collective intelligence within human societies.
GumbelSoft: Diversified Language Model Watermarking via the GumbelMax-trick
Large language models (LLMs) excellently generate human-like text, but also raise concerns about misuse in fake news and academic dishonesty.
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.
TravelPlanner: A Benchmark for Real-World Planning with Language Agents
Are these language agents capable of planning in more complex settings that are out of the reach of prior AI agents?
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.
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.
Piecing Together Clues: A Benchmark for Evaluating the Detective Skills of Large Language Models
We introduces the DetectBench, a reading comprehension dataset designed to assess a model's ability to jointly ability in key information detection and multi-hop reasoning when facing complex and implicit information.
Adaptive Chameleon or Stubborn Sloth: Revealing the Behavior of Large Language Models in Knowledge Conflicts
By providing external information to large language models (LLMs), tool augmentation (including retrieval augmentation) has emerged as a promising solution for addressing the limitations of LLMs' static parametric memory.
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.
Say What You Mean! Large Language Models Speak Too Positively about Negative Commonsense Knowledge
Large language models (LLMs) have been widely studied for their ability to store and utilize positive knowledge.
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.
Harnessing Knowledge and Reasoning for Human-Like Natural Language Generation: A Brief Review
The rapid development and application of natural language generation (NLG) techniques has revolutionized the field of automatic text production.
Converge to the Truth: Factual Error Correction via Iterative Constrained Editing
Given a possibly false claim sentence, how can we automatically correct it with minimal editing?
Unsupervised Explanation Generation via Correct Instantiations
The major difficulty is finding the conflict point, where the statement contradicts our real world.
Neighbors Are Not Strangers: Improving Non-Autoregressive Translation under Low-Frequency Lexical Constraints
To this end, we propose a plug-in algorithm for this line of work, i. e., Aligned Constrained Training (ACT), which alleviates this problem by familiarizing the model with the source-side context of the constraints.
E-KAR: A Benchmark for Rationalizing Natural Language Analogical Reasoning
Holding the belief that models capable of reasoning should be right for the right reasons, we propose a first-of-its-kind Explainable Knowledge-intensive Analogical Reasoning benchmark (E-KAR).
Unsupervised Editing for Counterfactual Stories
We also propose a new metric to alleviate the shortcomings of current automatic metrics and better evaluate the trade-off.
Probabilistic Graph Reasoning for Natural Proof Generation
In this paper, we propose PRobr, a novel approach for joint answer prediction and proof generation.
LOREN: Logic-Regularized Reasoning for Interpretable Fact Verification
The final claim verification is based on all latent variables.
Ensuring Readability and Data-fidelity using Head-modifier Templates in Deep Type Description Generation
A type description is a succinct noun compound which helps human and machines to quickly grasp the informative and distinctive information of an entity.
CN-Probase: A Data-driven Approach for Large-scale Chinese Taxonomy Construction
Taxonomies play an important role in machine intelligence.
