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9,568 papers
Across four system papers, the linked promotional page mainly helped identify what was being sold and added little to compliance-risk classification, which exposed sensitivity to rare labels, advertiser overlap across splits and substantial variation in the ST3 labels.
Jointly fine-tuning an LLM on meeting-summarisation corpora of widely varying size raises a question that prior work leaves confounded: when a domain-balanced training mixture helps, is the gain due to the distribution of tokens across domains, or merely to the volume of data seen? We disentangle these factors by const...
A per-token logits mask is applied that deterministically eliminates single-query column-use violations on the supported SQL fragment in a single decoding pass and achieves 0% Leakage Rate and Coverage up to 88.7% on Spider-CU, while staying within +10% tokens of direct prompting.
This work proposes a case-specific dynamic rubric framework that adaptively constructs MQM evaluation spaces for individual translation instances while dynamically selecting suitable subtype spaces and evaluation granularity for different cases.
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JetSpec is proposed, a head-based SD framework that combines one-forward drafting efficiency with branch-wise causal conditioning that enables JetSpec to convert larger draft budgets into longer accepted prefixes and higher end-to-end speedup.
The results suggest that for state-of-the-art LLMs, identifying a solution to the problem is insufficient, and reliably executing the resulting plan still poses a distinct challenge.
One of the most central aspects of language processing is the ability to trade off between stored representations and abstract knowledge: one must retrieve stored representations, but also generate novel ones by applying productive rules. While recent work has examined abstract knowledge in language models, holistic st...
The first user-centric benchmark grounded in real user feedback signals for evaluating preference alignment and dialogue generation is presented, demonstrating that user feedback prediction is a learnable capability and revealing different aspects that influence user experience.
This work ventures deep into detokenization using activation patching in controlled paired experiments that isolate the contribution of different model components, localizing English detokenization in Llama2-7B to a two-stage process at Layer 1.
ReadingMachine is a computational methodology for structured corpus reading that uses large language models to perform bounded reading operations over entire document collections. Rather than relying on retrieval or recursive summarization, the approach decomposes analysis into inspectable stages including insight extr...
Large language model (LLM) agents increasingly rely on external experience to continually adapt to changing environments without modifying their underlying models. Recent experience mechanisms have demonstrated promising results across diverse tasks. However, their effectiveness is typically evaluated within individual...
DySem is proposed, a novel training-free framework that investigates more semantic-related internal components of LLMs via multilingual consensus, and shifts away from static representation spaces in favor of dynamic, sample-specific semantic dimensions by constructing text-dependent joint semantic set and computes sim...
Natural Language Processing
Our most capable vision-language-action model enhances robot dexterity, reliability, and safety
A Blog post by Ai2 on Hugging Face
A Blog post by IBM Research on Hugging Face
Flint-interactive gives AI agents a language for creating interactive visualizations. Click a chart, filter data, highlight related content, and explore beyond the view the author originally chose. The post Flint-interactive: A language for creating interactive data visualizations appeared first on Microsoft Research.
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