Search Results for author:
Found 12 papers, 7 papers with code
MetaScientist: A Human-AI Synergistic Framework for Automated Mechanical Metamaterial Design
The discovery of novel mechanical metamaterials, whose properties are dominated by their engineered structures rather than chemical composition, is a knowledge-intensive and resource-demanding process.
FamiCom: Further Demystifying Prompts for Language Models with Task-Agnostic Performance Estimation
One popular approach is using perplexity as a way to measure models' familiarity with the prompt.
Rewarded Region Replay (R3) for Policy Learning with Discrete Action Space
We found that R3 significantly outperforms PPO in Minigrid environments with sparse rewards and discrete action space, such as DoorKeyEnv and CrossingEnv, and moreover we found that the improvement margin of our method versus baseline PPO increases with the complexity of the environment.
Red Teaming Language Models for Processing Contradictory Dialogues
To mitigate this issue, this study explores a novel contradictory dialogue processing task that aims to detect and modify contradictory statements in a conversation.
BLINK: Multimodal Large Language Models Can See but Not Perceive
We introduce Blink, a new benchmark for multimodal language models (LLMs) that focuses on core visual perception abilities not found in other evaluations.
Deceptive Semantic Shortcuts on Reasoning Chains: How Far Can Models Go without Hallucination?
During the construction of the evidence, we purposefully replace semantic clues (entities) that may lead to the correct answer with distractor clues (evidence) that will not directly lead to the correct answer but require a chain-like reasoning process.
Affective and Dynamic Beam Search for Story Generation
Storytelling's captivating potential makes it a fascinating research area, with implications for entertainment, education, therapy, and cognitive studies.
Does Your Model Classify Entities Reasonably? Diagnosing and Mitigating Spurious Correlations in Entity Typing
Due to shortcuts from surface patterns to annotated entity labels and biased training, existing entity typing models are subject to the problem of spurious correlations.
Unified Semantic Typing with Meaningful Label Inference
Semantic typing aims at classifying tokens or spans of interest in a textual context into semantic categories such as relations, entity types, and event types.
Ranked #3 on
Relation Extraction
on TACRED
Ultra-fine Entity Typing with Indirect Supervision from Natural Language Inference
The task of ultra-fine entity typing (UFET) seeks to predict diverse and free-form words or phrases that describe the appropriate types of entities mentioned in sentences.
Ranked #1 on
Entity Typing
on FIGER
COVID-19 Literature Knowledge Graph Construction and Drug Repurposing Report Generation
To combat COVID-19, both clinicians and scientists need to digest vast amounts of relevant biomedical knowledge in scientific literature to understand the disease mechanism and related biological functions.
Comprehensive Named Entity Recognition on CORD-19 with Distant or Weak Supervision
We created this CORD-NER dataset with comprehensive named entity recognition (NER) on the COVID-19 Open Research Dataset Challenge (CORD-19) corpus (2020-03-13).
