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 246
Mining Legal Arguments in U.S. Corporate Case Law
Legal argument mining supports passage classification, retrieval, and argument completion.Conduct Under Pressure: What Sixty Language Models Do When a User Pushes
We study what LLMs do when a user applies pressure in an uncomfortable situation: a user insists, begs, flatters or grieves, and the model gives up a correct fact, writes a document it should…Universal Fractal Natural Language Decision Map: Real-Time Edge Triage Across Heterogeneous Domains
Deploying Large Language Models for runtime operational triage incurs prohibitive latency (>100-500 ms), high VRAM requirements (>4-8 GB), and excessive energy dissipation.CTRL: Control-Based Time Series Forecasting with LLM-Guided Residual Learning
Time series forecasting underpins critical decision-making across diverse domains.Judging a Review by its Cover: A Reliability Analysis of LLM-based Peer Review Evaluation Metrics
Peer-review evaluation is increasingly being automated with LLM-as-a-judge metrics, but this creates a measurement risk.Knowing When to Trust Images: Reliability-Aware Multi-modal Entity Alignment
The visual modality, i.e., images, plays a key role in multi-modal entity alignment (MMEA).LLM-Based FORM Code Generation with Verification-Driven Fine-Tuning
FORM is a domain-specific symbolic manipulation language widely used in particle physics for processing the very large algebraic expressions arising from multi-loop Feynman diagram calculations.Machine-Interpretable Information: Compiling Documents into Searchable and Readable Protocol States
Long-context language models interface with external knowledge through raw natural language.One to More, More to One: Category-Aware Iterative Expert Training for Software Engineering Agents
Repository-level software engineering (SWE) comprises heterogeneous task categories, whose progress under pooled agentic reinforcement learning can be uneven: gains in some categories coincide with…MuLA-Bench: A Multilingual Long-Form Audio Understanding Benchmark via Multi-Tier Auditing
Long-form audio performance is often summarized by context length and aggregate accuracy, obscuring how language, evidence, and task jointly shape difficulty.Tool-Augmented On-Policy Distillation for LLM Domain Adaptation in Sequence-Based Omics Tasks
Multi-omics sequences contain complex biological patterns, yet deciphering their mechanisms for automated scientific discovery remains challenging.PSD: Pseudo Self-Distillation of Memory Representation Capabilities for LLM Agents
Memory systems are becoming a core component of LLM agents, but constructing and maintaining memory remains expensive because it relies on repeated calls to large proprietary language models.Long-Tail Rebalancing for Non-Verbal Vocalization-Aware ASR: A Track 1 System for the NVVSpeech Challenge
Non-verbal vocalizations (NVVs) carry important paralinguistic information but are often omitted by conventional automatic speech recognition (ASR) systems.Perplexity Predicts Protection: Choosing Pretrained Backbones for Worst-Client Fairness in Federated Parameter-Efficient Fine-Tuning
Federated learning lets multiple parties train a shared model without pooling their data, but a client with far less data than the others can end up poorly served even when the group's average…Propose, Verify, Commit: Evidence-Grounded Memory for Long-Horizon Multi-Actor Conversations
Long-horizon conversational memory is especially challenging in multi-actor settings, where relevant evidence is distributed across participants and contexts and previously established information…RPMem: Learning Long-Term Recurrent Parametric Memory Across Sessions for LLM Agents
Long-running LLM agents require memory that persists and evolves across sessions.BabelArena: A Large-Scale Multilingual Benchmark for LLM Agents
Large language model (LLM) agents increasingly execute multi-step workflows through tool use and interaction with users and environments.Paragraph Boundaries Are Not White Space:Compression Depth as the Signature of Hierarchical Structure
Standard positional encodings represent position as a one-dimensional reading-order coordinate, but reading order alone does not determine hierarchical textual structure.Contributions to the hierarchy of probabilistic languages
We reconsider the theory of probabilistic formal languages generated by n-gram models and by probabilistic context-free grammars (PCFGs).VibeMemBench: Evaluating Memory Systems for Coding Agents on Real Repository Coding Tasks
Coding agents operate on real repository coding tasks, and persistent memory systems promise to reuse experience across tasks.