AI & Machine Learning · Computer Science & AI
Computation & Language / NLP
The newest papers in Computation & Language / NLP that ReadSearch has read, newest first. Each links to its own page, with its authors, date, where it was published and the original.
The newest 5,000 papers, from 17 September 2026 to 5 November 2026: 5,000 arXiv preprints.
Get the few papers worth your time in Computation & Language / NLP every morning.
Follow Computation & Language / NLP and ReadSearch reads its new papers each day, then brings you the few worth reading, each with its key finding in a sentence.
Newest papers, page 29
Reading-Level Verification of Kanji Words in Japanese Financial Speech Synthesis
Few-shot voice cloning makes it cheap to produce daily Japanese financial commentary with several synthetic speakers, but kanji words with more than one reading, such as the word for "market" (shijo…Reasoning or Pattern Exploitation? Mechanistic Insights from RL-Trained Language Models
Large language models (LLMs) are increasingly described as acquiring "reasoning" skills after reinforcement learning with verifiable rewards.XLaw-JP-27B: A Lightweight Open Model Specialized for Japanese Law
We present XLaw-JP-27B, an open-weight model specialized for Japanese law that runs on a single 48\,GB GPU under the Apache~2.0 licence.AgentHeal: Evaluating Goal-Preserving Resource Recovery of Web Agents under Access Barriers
Large language model (LLM) agents have demonstrated strong capabilities in automating complex information-seeking and transactional tasks across the open web.Grounding Multimodal Reasoning with Evidence-Ablated Negatives
Reinforcement learning with verifiable rewards (RLVR) has become a powerful tool for improving multimodal reasoning.Unlimited OCR Works 2
Unlimited OCR ushers the era of long-horizon parsing, substantially mitigating the growth of working memory as document lengthens.Does the Citation Matter? Quality, Grounding, and Physician-Rubric Accuracy of Google's AI Overviews for Medical Information
Google's AI Overviews (AIOs) are the first result users encounter when searching the web, shifting the work of selecting and evaluating sources from the user to Gemini.Cord: Confidence-Anchored Order Residual Decoding for Masked Diffusion Language Models
The decoding order of masked diffusion language models (dLLMs) can substantially affect generation quality, yet common decoders typically apply the same reveal rule throughout generation.What Makes Medical Examination Items Difficult? Using Large Language Models to Explore Patterns Associated With Empirical Item Difficulty
Research on medical item difficulty has largely focused on prediction rather than on identifying interpretable patterns associated with empirical difficulty.Robustness of Chatbot LLM Judgments of Presidential Actions and Hypothetical Reforms
Chatbots are increasingly consulted about public affairs, and their judgments of policies are useful only if they are robust.How Specific Do I Need to Be? Effects of User Query Underspecification on Deep Research Agents
Deep research agents (DRAs) conduct long-horizon reasoning, search, and literature synthesis to provide long-form answers to complex, domain-specific questions.Well-Specified and Well-Tested? Assessing SWE-bench-Style Datasets with a Self-Evolving Agent
Large language models (LLMs) have shown strong performance on software engineering (SE) tasks, driving the need for high-quality datasets for reliable training and evaluation.Diagnosing the Reference Gap: What Visual Scaffolds Can and Cannot Fix in Multimodal Reasoning
Multimodal large language models can recognize visual content yet struggle to reason reliably over it across multiple steps.ARBITRA: Robust Document-Level ATT&CK Extraction via Multi-Expert Argumentation
Cyber threat intelligence (CTI) reports describe adversary behavior in natural language, but converting them into structured MITRE ATT&CK mappings remains difficult: existing methods decompose…Integrating Heterogeneous Echocardiography AI Outputs in Language Space: Learnable Late Fusion with a Supervised LLM
View- and target-specific echocardiography AI models capture useful but complementary information and may not achieve sufficient predictive performance in isolation.Lost in the Latent Space: How Code Embeddings Represent Functional Intent and Implementation Fidelity
Code embedding models have become a key building block for many software engineering applications, yet their internal representations remain poorly understood.Raincheck: Deferred Multimodal Prefill for Efficient Multi-Turn MLLM Inference
Multi-turn conversations with multimodal large language models (MLLMs) reuse input context, but long multimodal inputs increase time to first token (TTFT).Red-Teaming Large Language Models in Low-Resource African Languages: A Case Study of Yoruba and Nigerian Pidgin
As large language models (LLMs) become more widespread in Africa, their safety in low-resource languages remains largely untested since most red-teaming work focuses on English.Evaluating Cultural Knowledge Editing in Vision-Language Models
Current Vision-Language Models (VLMs) frequently fail to recognize culture-specific concepts, especially from underrepresented regions.Incentivizing Self-Learning in Large Language Models via Reinforcement Learning
Large language models (LLMs) draw on parametric knowledge and retrieval-augmented generation (RAG) to solve knowledge-intensive tasks.