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Found 20 papers, 12 papers with code
The AISP-SJTU Simultaneous Translation System for IWSLT 2022
This paper describes AISP-SJTU’s submissions for the IWSLT 2022 Simultaneous Translation task.
Do LLM Evaluators Prefer Themselves for a Reason?
Large language models (LLMs) are increasingly used as automatic evaluators in applications such as benchmarking, reward modeling, and self-refinement.
Self-Evolving Multi-Agent Collaboration Networks for Software Development
To extend coding capabilities beyond function-level tasks to more challenging software-level development, we further propose rSDE-Bench, a requirement-oriented software development benchmark, which features complex and diverse software requirements along with automatic evaluation of requirement correctness.
A Survey on the Honesty of Large Language Models
Honesty is a fundamental principle for aligning large language models (LLMs) with human values, requiring these models to recognize what they know and don't know and be able to faithfully express their knowledge.
Lifelong Histopathology Whole Slide Image Retrieval via Distance Consistency Rehearsal
Content-based histopathological image retrieval (CBHIR) has gained attention in recent years, offering the capability to return histopathology images that are content-wise similar to the query one from an established database.
ToolBeHonest: A Multi-level Hallucination Diagnostic Benchmark for Tool-Augmented Large Language Models
To address this challenge, we introduce a comprehensive diagnostic benchmark, ToolBH.
HoLLMwood: Unleashing the Creativity of Large Language Models in Screenwriting via Role Playing
Generative AI has demonstrated unprecedented creativity in the field of computer vision, yet such phenomena have not been observed in natural language processing.
ChartMimic: Evaluating LMM's Cross-Modal Reasoning Capability via Chart-to-Code Generation
We introduce a new benchmark, ChartMimic, aimed at assessing the visually-grounded code generation capabilities of large multimodal models (LMMs).
FedLLM-Bench: Realistic Benchmarks for Federated Learning of Large Language Models
Addressing this, we propose FedLLM-Bench, which involves 8 training methods, 4 training datasets, and 6 evaluation metrics, to offer a comprehensive testbed for the FedLLM community.
Unchosen Experts Can Contribute Too: Unleashing MoE Models' Power by Self-Contrast
In MoE, each token in the input sequence activates a different subset of experts determined by a routing mechanism.
Adaptive Fair Representation Learning for Personalized Fairness in Recommendations via Information Alignment
The existing works often treat a fairness requirement, represented as a collection of sensitive attributes, as a hyper-parameter, and pursue extreme fairness by completely removing information of sensitive attributes from the learned fair embedding, which suffer from two challenges: huge training cost incurred by the explosion of attribute combinations, and the suboptimal trade-off between fairness and accuracy.
Federated Learning Empowered by Generative Content
In this paper, we propose a novel FL framework termed FedGC, designed to mitigate data heterogeneity issues by diversifying private data with generative content.
AutoConv: Automatically Generating Information-seeking Conversations with Large Language Models
Information-seeking conversation, which aims to help users gather information through conversation, has achieved great progress in recent years.
Question Answering as Programming for Solving Time-Sensitive Questions
Question answering plays a pivotal role in human daily life because it involves our acquisition of knowledge about the world.
Ranked #1 on
Question Answering
on TempQuestions
(F1 metric)
NER-to-MRC: Named-Entity Recognition Completely Solving as Machine Reading Comprehension
Named-entity recognition (NER) detects texts with predefined semantic labels and is an essential building block for natural language processing (NLP).
Solving Math Word Problems via Cooperative Reasoning induced Language Models
This inspires us to develop a cooperative reasoning-induced PLM for solving MWPs, called Cooperative Reasoning (CoRe), resulting in a human-like reasoning architecture with system 1 as the generator and system 2 as the verifier.
Ranked #114 on
Arithmetic Reasoning
on GSM8K
Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice Perspective
We propose a new paradigm for zero-shot learners that is format agnostic, i. e., it is compatible with any format and applicable to a list of language tasks, such as text classification, commonsense reasoning, coreference resolution, and sentiment analysis.
Fengshenbang 1.0: Being the Foundation of Chinese Cognitive Intelligence
We hope that this project will be the foundation of Chinese cognitive intelligence.
Molecular Substructure-Aware Network for Drug-Drug Interaction Prediction
Concomitant administration of drugs can cause drug-drug interactions (DDIs).
REAPS: Towards Better Recognition of Fine-grained Images by Region Attending and Part Sequencing
Fine-grained image recognition has been a hot research topic in computer vision due to its various applications.
