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Found 18 papers, 7 papers with code
Interpretable Robotic Manipulation from Language
Natural language, moreover, serves as the primary medium through which humans acquire new knowledge, presenting a potentially intuitive bridge for translating concepts understandable by humans into formats that can be learned by machines.
Scrutinize What We Ignore: Reining Task Representation Shift In Context-Based Offline Meta Reinforcement Learning
Previous context-based approaches predominantly rely on the intuition that maximizing the mutual information between the task and the task representation ($I(Z;M)$) can lead to performance improvements.
A Trembling House of Cards? Mapping Adversarial Attacks against Language Agents
There is a surprisingly large gap between the speed and scale of their development and deployment and our understanding of their safety risks.
Dual-View Visual Contextualization for Web Navigation
Automatic web navigation aims to build a web agent that can follow language instructions to execute complex and diverse tasks on real-world websites.
The Language Barrier: Dissecting Safety Challenges of LLMs in Multilingual Contexts
As the influence of large language models (LLMs) spans across global communities, their safety challenges in multilingual settings become paramount for alignment research.
GPT-4V(ision) is a Generalist Web Agent, if Grounded
The recent development on large multimodal models (LMMs), especially GPT-4V(ision) and Gemini, has been quickly expanding the capability boundaries of multimodal models beyond traditional tasks like image captioning and visual question answering.
MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI
We introduce MMMU: a new benchmark designed to evaluate multimodal models on massive multi-discipline tasks demanding college-level subject knowledge and deliberate reasoning.
Mind2Web: Towards a Generalist Agent for the Web
We introduce Mind2Web, the first dataset for developing and evaluating generalist agents for the web that can follow language instructions to complete complex tasks on any website.
Flatness-Aware Prompt Selection Improves Accuracy and Sample Efficiency
We provide theoretical foundations for this metric and its relationship with other prompt selection metrics, providing a comprehensive understanding of existing methods.
Explaining Imitation Learning through Frames
As one of the prevalent methods to achieve automation systems, Imitation Learning (IL) presents a promising performance in a wide range of domains.
Genetic Imitation Learning by Reward Extrapolation
Imitation learning demonstrates remarkable performance in various domains.
GANExplainer: GAN-based Graph Neural Networks Explainer
With the rapid deployment of graph neural networks (GNNs) based techniques into a wide range of applications such as link prediction, node classification, and graph classification the explainability of GNNs has become an indispensable component for predictive and trustworthy decision-making.
An Empirical Study on Finding Spans
We present an empirical study on methods for span finding, the selection of consecutive tokens in text for some downstream tasks.
Multilingual Coreference Resolution in Multiparty Dialogue
Existing multiparty dialogue datasets for entity coreference resolution are nascent, and many challenges are still unaddressed.
Learn To Remember: Transformer with Recurrent Memory for Document-Level Machine Translation
We conduct experiments on three popular datasets for document-level machine translation and our model has an average improvement of 0. 91 s-BLEU over the sentence-level baseline.
Exploring Generalization Ability of Pretrained Language Models on Arithmetic and Logical Reasoning
To quantitatively and intuitively explore the generalization ability of pre-trained language models (PLMs), we have designed several tasks of arithmetic and logical reasoning.
Imitation Learning: Progress, Taxonomies and Challenges
Imitation learning aims to extract knowledge from human experts' demonstrations or artificially created agents in order to replicate their behaviors.
SemEval-2021 Task 4: Reading Comprehension of Abstract Meaning
Given a passage and the corresponding question, a participating system is expected to choose the correct answer from five candidates of abstract concepts in a cloze-style machine reading comprehension setup.
