Regional accent cues can be captured under matched conditions, but it remains unclear whether they persist between read and spontaneous speech. We study RVG1, with 500 German speakers from nine regions, comparing ten speech representations on regional classification and continuous geolocation under matched conditions a...
P. A. Pérez-Toro, Tomás Arias-Vergara, Annette Schwarz et al.· 0 citations
In this paper, we evaluate open-source generative LLMs on legal Natural Language Inference (NLI). Legal inspectorial processes take place in specific domains and often deal with confidential data. This creates a need for working with local models that do not require labeled training data. We evaluate our models on the...
Farrukh Baratov, Niki van Stein, Suzan Verberne· 0 citations
Long-context large language models (LLMs) have demonstrated strong capabilities across a wide range of tasks, but the growing KV cache introduces substantial memory and inference overhead. Existing one-shot KV cache compression methods typically commit to irreversible eviction immediately after prefill, before any sign...
Zhe Wang, Jia-Kai Li, Yu-Jia Sun et al.· 0 citations
Statistically valid estimation of racial and ethnic disparities often requires inferring the probability that an individual belongs to a particular racial or ethnic group given only their name and geographic location. The standard approach, Bayesian Improved Surname Geocoding (BISG), relies on group population frequenc...
Kyla Chasalow, Noah Dasanaike, Kosuke Imai· 0 citations
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Language-model systems batch questions for throughput, but unrelated questions should not change a target's answer when its input and numerical execution are fixed. We study compression of the key and value cache, which stores attention representations reused during generation. With request-local groups, Transformers'...
Seunghui Jwa, Minsu Oh, Chanjun Park et al.· 0 citations
During language acquisition, bilingual children are regularly exposed to code-switched input and use it as a cognitive scaffold to accelerate vocabulary growth and cross-linguistic syntactic mapping. In contrast, computational bilingual models are conventionally pretrained on interleaved monolingual corpora. While intr...
Zhuojing Huang, Luise Pohlmann, Lisa Beinborn· 0 citations
Realistic environment replicas are increasingly valuable for training and evaluating LLM agents, yet the original systems may be inaccessible or impractical to reproduce. We explore agentic language world modeling: rather than rebuilding an executable environment, a world model agent serves as the environment for a tas...
Quan-Yu Long, Xiao Chen, Jian-Da Chen et al.· 0 citations
Large Language Model (LLM) assistants routinely decide whether they can trust users and third parties whose competence, intentions, and integrity they cannot verify. This uncertainty matters for safety, as trusting the wrong party can lead an agent to comply with harmful requests or act on malicious instructions encoun...
Théo Lasnier, Romain Froger, Maxence Lasbordes et al.· 0 citations
D-Loop is proposed, which introduces \emph{intra-block causal conditioning} within the original diffusion drafter without additional model components, and can beat DFlash and DSpark on Qwen3-4B and Qwen3-8B with obvious gains.
Ke-Cheng Chen, Yu-Yang He, Cheng Gong et al.· 0 citations
With the rapid development of artificial intelligence, the emergence of various Large Language Models (LLMs) has created a rich model ecosystem. However, this also brings a key challenge: how to select the optimal model for a specific user query. LLM routing addresses this need by dynamically assigning queries to the m...
Yao Lu, Zhai-Yuan Ji, Ya-Xin Gao et al.· 0 citations
Tokenizer-free language models remove the inductive bias of fixed tokenizers by modeling text directly as bytes, but the resulting longer sequences substantially increase computation and eliminate explicit text abstractions. We ask whether this additional computation can be useful, and whether standard Transformers can...
Jie Wang, Shi-Wei Luo, Qi Zhang et al.· 0 citations
Verifier-guided decoding can prevent harmful reasoning steps from contaminating subsequent generation, but typically relies on an external learned verifier. We ask whether a language model can instead reject its own bad reasoning steps. We define a prefix's recoverability as the probability that the frozen generator ca...
Si-Heng Xiong, Xiaoze Liu, Yi-Qiao Jin et al.· 0 citations
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.
