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579 In this paper, we have proposed a novel counter- factual framework CLEVER for debiasing fact- checking models. Unlike existing works, CLEVER is augmentation-free and mitigates …
Alias-Free Mamba Neural Operator | OpenReview
Sep 25, 2024 · To counteract the dilemma, we propose a mamba neural operator with O (N) computational complexity, namely MambaNO. Functionally, MambaNO achieves a clever …
Weakly-Supervised Affordance Grounding Guided by Part-Level...
Jan 22, 2025 · In this work, we focus on the task of weakly supervised affordance grounding, where a model is trained to identify affordance regions on objects using human-object …
DEBERTA: DECODING-ENHANCED BERT WITH …
Jan 12, 2021 · Recent progress in pre-trained neural language models has significantly improved the performance of many natural language processing (NLP) tasks. In this paper we propose a …
MIND over Body: Adaptive Thinking using Dynamic Computation
Jan 22, 2025 · Clever use of intermediate activations to assess input complexity. Should be able to work with existing architectures making engineering it for downstream real-world use cases …
KooNPro: A Variance-Aware Koopman Probabilistic Model …
Jan 22, 2025 · The probabilistic forecasting of time series is a well-recognized challenge, particularly in disentangling correlations among interacting time series and addressing the …
Training Large Language Model to Reason in a Continuous …
Sep 26, 2024 · Large language models are restricted to reason in the “language space”, where they typically express the reasoning process with a chain-of-thoughts (CoT) to solve a …
Faster Cascades via Speculative Decoding | OpenReview
Jan 22, 2025 · Cascades and speculative decoding are two common approaches to improving language models' inference efficiency. Both approaches interleave two models, but via …
Reasoning of Large Language Models over Knowledge Graphs …
Jan 22, 2025 · While large language models (LLMs) have made significant progress in processing and reasoning over knowledge graphs, current methods suffer from a high non-retrieval rate. …
Oscillatory State-Space Models | OpenReview
Jan 22, 2025 · We propose Linear Oscillatory State-Space models (LinOSS) for efficiently learning on long sequences. Inspired by cortical dynamics of biological neural networks, we base our …
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