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Computation & Language / NLP
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The newest 5,000 papers, from 17 September 2026 to 5 November 2026: 5,000 arXiv preprints.
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Newest papers, page 25
S2TDR: Structured Multimodal Reconstruction for Sticker-Aware Dialogue Understanding
Stickers are widely used in social media dialogues to express affect, stance, and intent beyond literal text.TraceSpec: Understanding and Improving Speculative Decoding for LLM Agents
LLM agents execute tasks through repeated model calls over evolving histories of reasoning, actions, and tool feedback.Beyond Response Scoring: An AI-aware Cognitive Supervision Framework for Automated Mathematical Short Answer Grading
Transformer-based language models have achieved remarkable success in automated short answer grading (ASAG).TRIDENT and SHAKTI: A Framework and Benchmark for Hindi AI-Text Detection
As Large Language Models (LLMs) become increasingly multilingual, distinguishing human-written from AI-generated text is essential for maintaining information integrity.SciGraphSelect: Auditable Scientific Data Selection through Knowledge--Reasoning Graphs
Scientific data selection is typically driven by relevance or utility scores, providing limited insight into why a document is retained.PsyInterviewee: Informational Invariance and Relational Adaptivity in Mental Health Interview Simulation
LLM-based simulated interviewees support interviewer training and the evaluation of mental health interviewing systems.In-Model Context Compression with Agentic Soft Tokens for Long-Horizon LLM Agents
Long-horizon LLM agents play an important role in solving complex and sustained tasks, with ever-growing interaction contexts.From Transcription to Reformulation: Defining and Benchmarking Grounded Generative Speech Recognition
Speech language models have expanded automatic speech recognition (ASR) from transcription to general speech-to-text generation.SERIAL-7: Deriving, Realizing, and Preserving Machine-Verifiable Outputs Across Representations
Large language models increasingly generate structured outputs consumed by programs and downstream systems, where semantic correctness alone does not guarantee reliable execution.What We Keep of What We Forget: Replacement Operators and Routing Semantics in Training-Free MoE Expert Pruning
Training-free expert pruning makes two decisions: which experts to remove, and what the layer computes when its router still selects a removed expert.Comparative Evaluation of LLM-Based Review Paradigms for Academic Paper Quality Assessment
Growing submission volumes have renewed interest in using large language models (LLMs) to support peer review.ProSearch: Benchmarking Multi-Constraint Protocol Retrieval in Experimental Science
In AI for Science scenarios, experimental design and method reproduction require retrieving protocols that satisfy multiple interdependent constraints, yet existing benchmarks lack systematic…SparseGDN: Chunk Sparse in Linear Attention
Gated Delta Networks (GDNs) offer linear-time sequence modeling, yet long-context prefill remains costly due to dense intra-chunk computation, recurrent-state updates, and intermediate state storage.Hybrid Computer Use: A Unified Programmatic, Semantic, and Visual Interface for General Agents
Computer-use agents increasingly tackle tasks ranging from everyday desktop activities to long-horizon professional workflows.BlindToChange: AI Agents Can Find Changes When Asked But Do They Look When Needed?
Given that AI agents can search the web broadly and deeply in real time, it is tempting to conclude that their outputs account for recent world events.A prospective randomized study of patient-centered AI for clinical visit preparation
Patients often arrive at brief, time-constrained clinical visits unsure of what to expect or ask, and millions of adults now turn to general-purpose AI chatbots to prepare beforehand.KV-Cache Patching: Tracing How and Where Fine-Tuned Behaviors Arise
Fine-tuning a language model changes how it responds, but where is this fine-tuned behavior instantiated?KEEPER: Learning Control-Sufficient Textual Memory for Long-Horizon LLM Agents
Recursive textual memory can carry earlier errors into later updates, yet task performance alone does not establish memory reliability.Sparse Text Diffusion under Dual Budgets: Context Connectivity and Expert Activation
Long-context diffusion repeatedly pays for both token interaction and feed-forward computation.Enhancing Sentiment Classification on Small Datasets through Data Augmentation and Transfer Learning
Small-scale sentiment classification often suffers from data scarcity, which limits the generalization ability of the models.