Paper-Conference

Non Verbis, Sed Rebus: Large Language Models Are Weak Solvers of Italian Rebuses
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BabyLM Challenge: Exploring the effect of variation sets on language model training efficiency
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Model Internals-based Answer Attribution for Trustworthy Retrieval-Augmented Generation
Ensuring the verifiability of model answers is a fundamental challenge for retrieval-augmented generation (RAG) in the question …
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Multi-property Steering of Large Language Models with Dynamic Activation Composition
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NeLLCom-X: A Comprehensive Neural-Agent Framework to Simulate Language Learning and Group Communication
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The SIFo Benchmark: Investigating the Sequential Instruction Following Ability of Large Language Models
Following multiple instructions is a crucial ability for large language models (LLMs). Evaluating this ability comes with significant …
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Democratizing Advanced Attribution Analyses of Generative Language Models with the Inseq Toolkit
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DecoderLens: Layerwise Interpretation of Encoder-Decoder Transformers
In recent years, several interpretability methods have been proposed to interpret the inner workings of Transformer models at different …
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Encoding of lexical tone in self-supervised models of spoken language
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IT5: Text-to-text Pretraining for Italian Language Understanding and Generation
We introduce IT5, the first family of encoder-decoder transformer models pretrained specifically on Italian. We document and perform a …
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