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 18 September 2026 to 6 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 234
Don't CLAP: Are Music-Text Models Bag-of-Words?
Text-to-music systems are assessed on audio quality and on how faithfully the music follows its prompt, and the CLAP score, the cosine similarity between a music-text model's audio and text…REALMS: An AI-Assistant Conversational System for Real-Time Exact Audience Sizing over High-Dimensional Nested Profiles
Audience sizing is a critical component of digital marketing.Probing Stability-Plasticity Tradeoffs in Agent Memory through Cognitive Experimental Paradigms
Agent memory systems are increasingly used to maintain long-term user preferences, task states and evolving facts, but current evaluations often collapse memory behavior into final-answer accuracy.Thinking Less to Simulate Better: Intuitive Prompting Improves LLM Agents Simulating Individual Social Media Reactions, Including Unfamiliar Content
Platform policies are increasingly tested on artificial users, making agent fidelity important.The Hard Part Comes After Search: Benchmarking Web Agents on Synthesizing, Organizing, and Displaying Knowledge
Existing computer-use agent benchmarks do not fully evaluate agents acting as assistants.Epstein Files Engine: Agentic Search for Investigative Journalism
On Jan.Robot Manipulation with GPT-6-Astra: Body Knowledge, Experience Reuse, Emergent Skills, and Sim2Real Transfer
General-purpose multimodal agents can write robot-control programs, but repeated exploration and model-mediated action selection can make execution slow.Optimal transport meets speech: a tutorial review
Optimal Transport (OT) provides a principled framework for comparing and transforming probability distributions while preserving geometric structure.Neurosymbolic Routing for Reliable Reasoning on Resource-Constrained Edge Devices
Running a language model on edge hardware provides private and low-latency reasoning without a network connection, and yet the small models that fit on such devices are unreliable on the tasks…Realize What Matters: Principled Context Representation for Large-Scale Reasoning
Solving complex tasks in domains such as science, medicine, law, and finance often requires assembling interdependent information scattered across vast, heterogeneous sources far beyond model…Beyond Overlap: Estimating the Causal Effect of Benchmark Exposure
Evidence that evaluation material entered training does not reveal how much it affected evaluation.Quieter Than the Room: Representation Drift and Task Robustness in Speech Encoders
Non-speech interference can change a speech representation without causing comparable task loss.Phonemizing User-Generated Text: A Benchmark, Taxonomy, and Compositional Approach
Text-to-speech systems increasingly process user-generated text (UGT) such as ppl and imo, whose pronunciation must be inferred from the canonical rather than surface form.LOCKR: A Hidden-State Trajectory-Guided Planner for Detecting and Repairing Stable-but-Wrong Lock-In in Diffusion Language Models
Diffusion language models generate text through iterative denoising, exposing intermediate trajectories before final answers are produced.Meet, Compare, or Abstain: LatWeave for Deterministic Multi-Hop Question Answering on Knowledge Lattices
Probabilistic question-answering systems -- whether large language models (LLMs) themselves, retrieval-augmented generation (RAG), or trained multi-hop retrievers -- conflate "what is known" and…Distilling Sequential Computation in Transformer Language Models
Transformer language models process sequences token by token in an autoregressive manner, making growing contexts increasingly expensive.UniDataAgent: An Ontology-Grounded Agent for Enterprise Question-to-Report Automation
Enterprise data agents must preserve organization specific semantics, not just translate questions into queries.Can One Adapted Model Do It All? Fine-Tuning Strategy Selection for Customer Support LLMs
Production customer-support systems often require LLMs to support multiple skills, such as intent classification, question answering, summarization, or tool-use decisions.CAVEAT: Towards Robust Computer-Use Agents in Incentive-Misaligned Environments
Computer-use agents (CUAs) increasingly act on behalf of users online.EnSIMem: Entity-Structured Indexing for Long-Term Agent Memory
An agent that interacts with users over long periods must recall facts, preferences, events, and changes from a continuously growing interaction history.