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 172
Ideological Stance Detection in a Low-Resource Language: Polarization in Bangladeshi Public vs Private University Discourse on Social Media
Public vs. private universities is a debatable issue, and it creates polarization on social media in Bangladesh.Saying, Not Knowing: Aggressively GGUF-Quantized Small Language Models Still Write Rare Words They Can No Longer Define
Post-training quantization to the GGUF format's mixed-precision K-quants is commonly how open-weight language models reach consumer hardware, yet its effect on fine-grained lexical competence is…Understanding and Mitigating Hallucination Escape in Tool-Using LLM Agents
Large language models (LLMs) increasingly serve as autonomous agents that invoke external tools.Large Language Models and Augmented Democracy
Artificial intelligence enables computational agents to represent political preferences and take part in collective decision-making.DV-Lens: Revealing the Functional Organization of Language Model Parameters
Understanding parameter functions helps elucidate the internal mechanisms of large language models (LLMs).Emoji-Emotion Ranking System Using Twitter Data
Nowadays, emojis are often replacing words.Homogeneous Semantic Alignment and Hierarchical Expert Routing for Radiology Report Generation
Radiology report generation (RRG) aims to convert medical images into diagnostic texts to assist in clinical decision-making and alleviate the workload of physicians.The Same Zero: Why Identical ASR Can Imply Different Guarantees in LLM-Agent Security
LLM-agent security has produced a dense landscape of defenses - prompt hardening, content filters, permission gates, sandboxes - yet no framework tells a deployer what a defense actually guarantees…Correctness Is a Direction: Geometric Answer Selection in Language Models
Answer correctness is encoded as a recoverable geometric direction in the hidden states of language models.Autonomous Structuring of Radiology Reports Across Modalities at Archive Scale Using an Open-Weight Large Language Model
To develop and evaluate an open-weight large language model (LLM) pipeline that converts an entire archive of free-text radiology reports into structured reports without human oversight.From Probe Scores to Alarm Policies: Operational Validity of Activation Monitors for Language-Model Agents
Activation probes can predict safety-relevant properties of language models with high area under the receiver-operating-characteristic curve (AUROC), but deployed agent monitors make thresholded…Strong Helps Weak: Directional Cross-Modal Alignment Transfer in Multi-modal LLMs
Multi-modal large language models (MLLMs) achieve strong modality understanding by pairing a large language model (LLM) with an encoder for a target modality such as vision, video, or audio.StegoMemory: Agentic Memory Acts as Covert Steganographic Channel
Is agentic memory robust against stealthy steganographic attacks?SIFT: Robust Meta-Faithfulness Verification of Chain-of-Thought Reasoning Under Distribution Shift
Chain-of-Thought (CoT) faithfulness detectors are widely used to audit reasoning models, yet a detector is itself a predictor whose verdicts are treated as stable properties.Stance Drift: How AI-mediated Communication Distorts Our Message
Large language models (LLMs) increasingly mediate human communication, from drafting emails to summarizing scientific reports, yet whether they faithfully preserve a speaker's position remains…Does Neural Complexity Improve Health Misinformation Detection? A Leakage-Controlled Cross-Corpus Benchmark
Increasing architectural complexity is often assumed to improve health misinformation detection, yet reported gains are difficult to interpret when studies use different corpora, preprocessing…Grounding Probes: Generator-Independent Hallucination Detection from Observer Model Hidden States
Detecting responses that retrieval-augmented generation does not ground in its context trades speed against accuracy: surface checks miss paraphrased fabrication, sampling-based methods cost extra…Extracting Persona Subspaces Through Iterative Nullspace Projection For Modulation
Large Language Models (LLMs) can adopt distinct personas to tune their semantics, expertise, and perspective to different users and tasks.Steering Speech-Language Models: Training-Free Task Specialization via Contrastive Activation Addition
Activation steering has proven effective for controlling the behavior of Large Language Models (LLMs) at inference time, but its application to SpeechLLMs remains new, and training-free steering…When Debate Helps: Proposal Supply and Verification-Aware Readout in Multi-Agent Reasoning
Multi-agent debate can improve reasoning, yet often fails to beat simple majority voting.