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20242026
most citedAligning with Logic: Measuring, Evaluating and Improving Logical Preference Consistency in Large Language Models

3 citations · 3 across the 17 of their papers we have counts for

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Showing 2025 · cs.CLShow all

7 papers · 2 filters

cs.CL2025

Beyond the Final Layer: Intermediate Representations for Better Multilingual Calibration in Large Language Models

Ej Zhou, Caiqi Zhang, Tiancheng Hu +4

Confidence calibration, the alignment of a model's predicted confidence with its actual accuracy, is crucial for the reliable deployment of Large Language Models (LLMs). However, t…

cs.CL2025

ReCoVeR the Target Language: Language Steering without Sacrificing Task Performance

Hannah Sterz, Fabian David Schmidt, Goran Glavaš +1

As they become increasingly multilingual, Large Language Models (LLMs) exhibit more language confusion, i.e., they tend to generate answers in a language different from the languag…

cs.CL2025

11Plus-Bench: Demystifying Multimodal LLM Spatial Reasoning with Cognitive-Inspired Analysis

Chengzu Li, Wenshan Wu, Huanyu Zhang +6

For human cognitive process, spatial reasoning and perception are closely entangled, yet the nature of this interplay remains underexplored in the evaluation of multimodal large la…

cs.CL2025

Quantifying Language Disparities in Multilingual Large Language Models

Songbo Hu, Ivan Vulić, Anna Korhonen

Results reported in large-scale multilingual evaluations are often fragmented and confounded by factors such as target languages, differences in experimental setups, and model choi…

cs.CL2025

Imagine while Reasoning in Space: Multimodal Visualization-of-Thought

Chengzu Li, Wenshan Wu, Huanyu Zhang +5

Chain-of-Thought (CoT) prompting has proven highly effective for enhancing complex reasoning in Large Language Models (LLMs) and Multimodal Large Language Models (MLLMs). Yet, it s…

cs.CL2025

Language Fusion for Parameter-Efficient Cross-lingual Transfer

Philipp Borchert, Ivan Vulić, Marie-Francine Moens +1

Limited availability of multilingual text corpora for training language models often leads to poor performance on downstream tasks due to undertrained representation spaces for lan…

cs.CL2025

Fleurs-SLU: A Massively Multilingual Benchmark for Spoken Language Understanding

Fabian David Schmidt, Ivan Vulić, Goran Glavaš +1

Spoken language understanding (SLU) is indispensable for half of all living languages that lack a formal writing system. Unlike for high-resource languages, for these languages, we…