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 99
ESG-Kor: A Korean Dataset for ESG-related Information Extraction and Practical Use Cases
With the expansion of pre-trained language model usage in recent years, the importance of datasets for performing tasks in specialized domains has significantly increased.DPA-MoE: A Runtime Precision Control Framework for MoE Inference
Mixture-of-Experts (MoE) models reduce computation by routing each token to a small set of experts, but each selected expert is still used at a fixed precision.Calibration Language Shapes Block-Influence Pruning in Multilingual Language Models
Block Influence (BI) ranks Transformer blocks for depth pruning from their input-output cosine change, but the ranking depends on the calibration distribution.Beyond Invariance: Factor-wise Selective Treatment of Shifts for Multimodal Learning
Distribution shifts pose a fundamental challenge to robust multimodal learning.Identifying Effective Strategies in Prompt Evolution for Stress and Emotion Prediction
Early stress detection and risk prediction are crucial for timely mental health assessment and support.Do Agents Need a New Kind of Paper? SPRA: Structured Paper Representation for Agents
Scientific agents must connect research problems, methods, and findings dispersed through narrative articles.HyCo: Hybrid Drafting for Cost-Efficient Mobile-Cloud Speculative Decoding
Device-cloud speculative decoding reduces server computation, but growing a deep draft tree with a small language model (SLM) requires repeated passes on a mobile neural processing unit (NPU).SITAR: A Situational Distortion Metric for Automatic Speech Recognition Evaluation
In automatic speech recognition (ASR), transcription errors with similar lexical or semantic discrepancies can have markedly different consequences for the situation conveyed by speech.Translation Circuit Discovery and Targeted Optimization for Low-Resource Multilingual Translation
Recent multilingual large language models achieve strong translation performance, yet the internal mechanisms responsible for low-resource multilingual translation remain insufficiently understood.Trajectory-Level Speculation with Semantic Verification for Tool-Using Agents
Large language model agents solve tasks through long sequences of tool calls, and the prevailing design has a single strong model generate every step, although many steps are routine enough for a…Can LLMs Tell Stories Out of Order? A Corpus and Benchmark for Nonlinear Narrative Generation
Every story has two orders: the order in which its events happen and the order in which they are told.OPRD: On-Policy Reminder Distillation for Long-Horizon Coding Agents
Reliable repository-level coding requires agents not only to generate correct code but also to preserve constraints and respond to tool feedback across long interactions.Decomposing Brain-LLM Alignment with Interpretable Semantic Representations
Large language models (LLMs) predict neural responses during naturalistic language comprehension, but the linguistic information underlying this brain alignment remains difficult to interpret.SCRIBE: Scalable Contextual Representations of Interpretable Brain-Grounded Semantics
Understanding how the human brain constructs meaning from real-world language remains a fundamental challenge, as semantics depend on context that varies in natural settings.Writability and the Pathway: A Controlled Study of Knowledge Injection into Addressed Memory
Addressed conditional memory provides a local surface for post-hoc knowledge injection, but a successful write need not transfer to a new question or preserve untargeted behavior.DialFork: Going Beyond Factuality to Evaluate Procedural Hallucination in Conversational Agents
Large language models (LLMs) deployed as conversational agents are increasingly expected to follow procedural logic.Rethinking the Role of Tool Graph Memory in Multi-Turn Tool Use
Large language model (LLM) agents solve complex tasks by calling external tools over multiple turns.Waypoint-OPD: Transferring RL-Induced Policy Shifts via Gated On-Policy Distillation
Policy-shift distillation reuses the difference between a teacher's log probabilities before and after reinforcement learning (RL) as supervision on student-generated trajectories.ContextLift: Breaking the Spurious Correlation Behind Conditional Emergent Misalignment
Finetuning a language model on narrowly misaligned data can make it broadly misaligned.Spurious Attention Heads in Vision Transformers: Mechanistic Identification of Annotation-Driven Bias in Medical Chest X-Ray Analysis
Vision Transformers deployed in medical imaging exploit spurious correlations, yet the internal mechanisms remain unidentified and impossible to fix.