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Computation & Language / NLP
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Newest papers, page 71
Give the Model a Finger: Developmentally Aligned Evaluation of Counting in Vision-Language Models
Vision-language models (VLMs) are exact on small sets and drift into estimation on larger ones, a profile reminiscent of children before they master counting.Are Linguistic and Arithmetic Circuits Dissociated in LLMs?
Large language models (LLMs) exhibit both knowledge of language, rendered by, for example, grammatical judgment ability, and abilities to perform tasks through language, such as math-word problem…ProVe: Proposer-Verifier Decoding
Speculative decoding accelerates autoregressive (AR) language models by letting a small model draft tokens serially and a large model verify them in parallel.SMART: Semantic Segment Mapping and Assessment of Recognition Transcripts with Contextual Rubrics
Word error rate (WER) assigns equal cost to lexical edits despite their different semantic consequences, while overall semantic scores cannot identify which individual errors alter the intended…SciDiagBench: A Type-Specific Benchmark for Human-Aligned Evaluation of Scientific Diagrams
Recent agents have demonstrated strong capabilities in generating images from textual prompts, motivating their utilization for scientific diagram generation.UvA-MT's Participation in the WMT26 General Translation Shared Task
This paper presents UvA-MT's submission to the WMT 2026 General Machine Translation shared task, competing in the unconstrained track across all 23 translation directions.From Tokens to Files: Multi-Granularity Detection and Localization of AI-Involved Code
The increasing use of large language models for code generation calls for methods that distinguish purely human-written code from AI-involved code: files in which any part, however small, was…Testing Associative Creativity in Humans and Multimodal LLMs with Difficult-to-Name Visual Stimuli
We investigate associative creativity in descriptions of abstract visual stimuli by humans and multimodal large language models (MLLMs).CollabSciReM: Aligning Language Models for Scientific Conversations via Science-Aware Reward Decomposition
Large Language Models (LLMs) are increasingly used as research collaborators for hypothesis refinement, methodological planning, and technical analysis across multi-turn interactions.Staged Continual Adaptation of Multimodal Foundation Models for Japanese Financial Documents
Staged post-training of multimodal foundation models chains vision-language alignment, reasoning distillation, and domain tuning, yet how each phase trades capabilities against the others remains…Polarity Blindness in LLM Safety: A Systematic Study of Negation, Antonym Substitution, and Adversarial Framing
Negation remains a persistent challenge for language models across NLP tasks and modalities.ACE-Compression: An Ability-Centric Evaluation of Compressed Large Language Models
Model compression makes large language models deployable, but today's evaluation tells an incomplete story.Why Do LLMs Accept Generics? Explaining Acceptability using Psycholinguistic and Model-Derived Factors
Psycholinguistic studies explore why humans accept some generic statements but reject others by showing that these judgments depend on more than how common a property is.From DQI to C-DQI: Automatic Codebook Generation and Evaluation for Measuring Computational Discourse Quality Index
Effective democratic deliberation is vital for civic engagement and the health of legislative institutions.Lost in Recovery: Demystifying Recovery Behavior of Computer-Use Agents via Goal-Oriented Action Replay
Recent advances in large (vision) language models have enabled computer-use agents that automate digital workflows via fine-grained keyboard and mouse operations.Adaptive Stopping of Streamed Reasoning for Language Model Agents
Reasoning-enabled language model agents can incur substantial computation before acting, although the reasoning needed varies across decisions.Building Telecom Language Models with RSOD: Domain Data, Specialist Post-Training, Memory-Conscious Distillation, and Networking Evaluation
Telecom language models must combine broad networking knowledge with specialist behavior across routing, broadband services, access technologies, and operational diagnostics while remaining…Beyond the Evidence Boundary: Behavioral Mirage Under Progressive Degradation in Medical VLMs
VLMs for medical image interpretation are typically evaluated on clean inputs, despite the progressive evidence loss that can occur in high stakes clinical settings.From RL Papers to Framework Code: Inclusion and Review in Seven Open-Source Training Frameworks
Practitioners use reinforcement learning methods for language models through training frameworks, so a method that a framework includes is one configuration change away for its users.Using Letter Positional Probabilities to Assess French Word Complexity
We use Letter Positional Probabilities (LPPs) to examine the orthographic differences between simple and complex French words.