News / #paper Tag Research papers 500 articles archived under #paper · RSS Sign in to follow arXiv — NLP / Computation & Language research 5d ago Probing for Long-Horizon Deductive Reasoning Capabilities in Language Models with Prolog arXiv:2610.11592v1 Announce Type: new Abstract: Current frontier LLMs can theoretically process long contexts with 1M tokens or more. But to what extent can they go beyond simple retrieval and perform deeper reasoning over such long contexts? We empirically investigate… 27 arXiv — NLP / Computation & Language research 5d ago Large Language Model Turnover Undermines Screening for Artificial Intelligence-Assisted Scientific Writing arXiv:2610.11599v1 Announce Type: new Abstract: Journals and conferences have begun to screen submitted manuscripts for text written using large language models (LLMs). The reliability of this screening rests on benchmark evaluations against a fixed set of LLM versions, while… 21 arXiv — NLP / Computation & Language research 5d ago UXBench Pro: Benchmarking Personalized User Experience in Multi-Turn Dialogue Interactions arXiv:2610.11638v1 Announce Type: new Abstract: Evaluating user experience (UX) with automated computational methods has gained increasing attention, supported by empirical evidence from UXBench. However, binary preference prediction provides limited insight, while relying on a… 8 arXiv — NLP / Computation & Language research 5d ago Phonologically Informed Tokenization for German Speech Recognition: A Cross-Domain Study arXiv:2610.11646v1 Announce Type: new Abstract: German is a morphologically rich language whose syllable structure is exceptionally well-predicted by the Knuth--Liang hyphenation algorithm. We ask whether phonologically informed tokenization can serve as a competitive target for… 10 arXiv — NLP / Computation & Language research 5d ago DIAL-OPD: Learning More from Fewer Tokens in On-Policy Distillation arXiv:2610.11659v1 Announce Type: new Abstract: On-policy distillation (OPD) supervises student-generated trajectories with token-level teacher signals. Its sampled-token variant avoids the cost of full-vocabulary probabilities. Yet we find that training on fewer tokens can… 31 arXiv — NLP / Computation & Language research 5d ago TRACE: Diagnosing Verifier Brittleness in Agentic Evaluation arXiv:2610.11678v1 Announce Type: new Abstract: Verifier scores now serve as both benchmark metrics and training rewards for large language model (LLM) agents, and a change in score is routinely read as a change in capability. It may instead reflect a change in the evaluation.… 29 arXiv — NLP / Computation & Language research 5d ago Structured Sentiment Analysis Using Sequence Labeling as Dependency Graph Parsing arXiv:2610.11695v1 Announce Type: new Abstract: This study addresses the problem of structured sentiment analysis, whose goal is to obtain a fine-grained sentiment graph where the nodes represent spans of sentiment holders, targets, and expressions, while the arcs define the… 30 arXiv — NLP / Computation & Language research 5d ago Thinking Inertia: LLMs Keep Thinking When Told Not To arXiv:2610.11765v1 Announce Type: new Abstract: Large Language Models (LLMs) increasingly ship with explicit "thinking modes", yet their counterpart, "no-thinking", has received far less attention. We study LLMs' no-thinking behavior along two axes. a. How to measure… 34 arXiv — NLP / Computation & Language research 5d ago Same Outcome, Different Evidence: Intent Recovery in LLM Safety Evaluation arXiv:2610.11766v1 Announce Type: new Abstract: Safety evaluations of large language models commonly summarize harmful-output behavior with attack success rate (ASR). Yet the same non-harmful outcome can arise for very different reasons. A model may recover a harmful task and… 26 arXiv — NLP / Computation & Language research 5d ago DPPM: Dual-Path Parametric Memory for Personalized Language Models arXiv:2610.11776v1 Announce Type: new Abstract: Long-term personalization requires language models to use interaction history to track users' preferences across sessions. Parametric memory encodes this interaction history into model parameters or adapters, reducing the need to… 30 arXiv — NLP / Computation & Language research 5d ago From Sparse Representations to Behavioral Insights for Multimodal Depression Assessment arXiv:2610.11787v1 Announce Type: new Abstract: Multimodal depression assessment offers a promising approach to analyzing behavioral patterns associated with depression. However, existing methods often rely on dense and opaque multimodal representations, making it difficult to… 26 arXiv — NLP / Computation & Language research 5d ago Easy to anticipate, hard to compute: boundary dependence finds the computed outputs that entropy patching misses arXiv:2610.11790v1 Announce Type: new Abstract: Byte-level language models such as the Byte Latent Transformer (BLT) group bytes into patches and run their large global model once per patch. BLT starts a patch where a small model's next-byte entropy is high, so global compute… 9 arXiv — NLP / Computation & Language research 5d ago Detecting Spin in Clinical Trials with Large Language Models arXiv:2610.11845v1 Announce Type: new Abstract: Spin in clinical trials includes reporting practices that distort the presentation of results. This is particularly critical in medicine, where spin is present in more than 50% of randomized controlled trials that fail to reach… 32 arXiv — NLP / Computation & Language research 5d ago Forms of LLM-Integrated Applications from LLM-Chats to Autonomous AI Agent System arXiv:2610.11899v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly embedded as components in software systems, marketed under labels such as chatbot, copilot, retrieval-augmented generation, workflow, coding agent and AI agent. Whether these labels… 36 arXiv — NLP / Computation & Language research 5d ago Can Decision Models Understand Stance? Evaluating Jev Against General-Purpose LLMs arXiv:2610.11901v1 Announce Type: new Abstract: Stance detection requires identifying an author's attitude toward a given target, sometimes based on conversational context. Jev, a specialized decision model designed for structured decision-making, offers an alternative to… 4 arXiv — NLP / Computation & Language research 5d ago Not Every Change Is Necessary: Recoverable Drift in Large Language Model Unlearning arXiv:2610.11915v1 Announce Type: new Abstract: Machine unlearning in large language models aims to remove unwanted knowledge while preserving the model's remaining capabilities. Although existing methods use retention objectives or restrict where edits occur, achieving the… 10 arXiv — NLP / Computation & Language research 5d ago Event-Centric Memory with Query-Aware Graph Augmentation for Long-Term Conversational Agents arXiv:2610.11920v1 Announce Type: new Abstract: For persistent and personalized conversational agents, memory systems can enable them to remember, update, and reason over long histories by storing past interactions and retrieving relevant information. Existing memory systems… 30 arXiv — NLP / Computation & Language research 5d ago When History Helps and Hurts: Selective History Use across Multimodal Turns arXiv:2610.11948v1 Announce Type: new Abstract: Reliable multimodal interaction depends on selective use of conversational history: an earlier question may remain relevant while its previous answer is outdated, whereas a current request may depend on historical evidence despite… 16 arXiv — NLP / Computation & Language research 5d ago MiMo-V2.6: Scaling Reinforcement Learning Towards Self-Improvement arXiv:2610.11959v1 Announce Type: new Abstract: Reinforcement learning (RL) is the central training paradigm for advancing large foundation models towards self-improvement. This report introduces the MiMo-V2.6 series, an omni-modal family that pushes the frontier of model… 36 arXiv — NLP / Computation & Language research 5d ago Specialized Decision Models vs. General-Purpose LLMs: Benchmarking Jev Across Knowledge, Reasoning, and Multilingual Tasks arXiv:2610.11978v1 Announce Type: new Abstract: Jev is a "System One" model that returns a choice among given options instead of generating text. We study how such a specialized decision model compares with general-purpose large language models (LLMs). We evaluate Jev on 13… 20 arXiv — NLP / Computation & Language research 5d ago Examining Social Attribution in LLM Reasoning: A Theory-Guided Probing Methodology arXiv:2610.12022v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly deployed in sociotechnical systems where social attribution, the reasoning process attributing external events to the causes and reasons of agents' social behaviors, plays a critical… 35 arXiv — NLP / Computation & Language research 5d ago Natural Language to First-Order Logic LLM-based Autoformalization arXiv:2610.12030v1 Announce Type: new Abstract: Large Language Models (LLMs) have renewed interest in autoformalization. Yet, when First-Order Logic (FOL) is considered as the target formalism, the field still lacks a unified task formulation and a systematic survey. This paper… 31 arXiv — NLP / Computation & Language research 5d ago ILM: An AI-Powered Storytelling Educational Tool arXiv:2610.12064v1 Announce Type: new Abstract: Digital technologies have made Islamic narratives more accessible, but existing platforms provide limited support for structured learning and comprehension of these stories, particularly in Arabic and multilingual settings. We… 20 arXiv — NLP / Computation & Language research 5d ago All Verdicts are Not Equal: Rethinking LLM Judge Reliability arXiv:2610.12083v1 Announce Type: new Abstract: LLM-as-a-Judge is the standard paradigm for NLP evaluation, yet its systemic reliability remains poorly understood despite being widely treated as a deterministic ground truth. We present a comprehensive reliability audit,… 34 arXiv — NLP / Computation & Language research 5d ago A persistent accuracy ceiling in automated verbal deception detection arXiv:2610.12118v1 Announce Type: new Abstract: Automated methods have been proposed to overcome the limitations of human verbal deception detection, but evidence remains fragmented across disciplines. We systematically reviewed 25 years of research (289 reports, 6,136… 13 arXiv — NLP / Computation & Language research 5d ago Rehearse Everything, Remember Nothing: Attic-KV Rehearses What Will Be Read arXiv:2610.12133v1 Announce Type: new Abstract: Many key-value (KV) caches are compressed before anyone knows what will be asked of them: a document cached for retrieval, a prompt prefix shared across requests, the memory of a long conversation. The prevailing approach scores KV… 22 arXiv — NLP / Computation & Language research 5d ago Language-Specific Effects of Tokenizer Choice in Multilingual Language Models arXiv:2610.12144v1 Announce Type: new Abstract: Tokenizer choice affects multilingual language modeling, but vocabulary capacity is finite and vocabulary size is often constrained: improving representation for some languages often comes at the expense of others. We therefore ask… 27 arXiv — NLP / Computation & Language research 5d ago SciTBERT: A family of chronologically consistent language models for scientific and technological language processing arXiv:2610.12207v1 Announce Type: new Abstract: Pre-trained transformer models are increasingly being used to study scientific and technological progress. Encoders tuned to paper or patent text outperform general-purpose models on downstream classification, regression, and… 38 arXiv — NLP / Computation & Language research 5d ago Language Models as AI Research World Models arXiv:2610.12235v1 Announce Type: new Abstract: AI research agents automate the cycle of proposing, implementing, and evaluating experiments, opening a path toward recursive self-improvement. Yet their ability to propose experiments outpaces their capacity to execute them in… 28 arXiv — NLP / Computation & Language research 5d ago TokenRouter: Efficient Serving System for Token-Level LLM Routing arXiv:2610.12242v1 Announce Type: new Abstract: Large language model (LLM) routing distributes inference work across different models, advancing the cost-quality Pareto frontier of LLM serving. While coarse-grained routing at the session or query level has been widely adopted in… 5 arXiv — NLP / Computation & Language research 5d ago EgoVoice: Proactive Spoken Assistance from Egocentric Multimodal Streams arXiv:2610.12248v1 Announce Type: new Abstract: Wearable augmented reality (AR) assistants are moving toward continuous real-world interaction, where they perceive the user's activity through first-person video and audio and provide timely spoken guidance without being… 20 arXiv — NLP / Computation & Language research 5d ago HarnessSQL: Harness-Native Training for SQL Agents in Realistic Database Environments arXiv:2610.12274v1 Announce Type: new Abstract: Text-to-SQL models are commonly trained to map questions directly to static queries, whereas real-world database agents operate through stateful, multi-turn interaction with live databases -- inspecting schemas, executing probe… 24 arXiv — NLP / Computation & Language research 5d ago VFold: Symmetry-Aware Cross-Layer Value Cache Compression arXiv:2610.12338v1 Announce Type: new Abstract: While caching key-value (KV) states accelerates Large Language Model (LLM) decoding, this cache can dominate memory usage at long context lengths. One solution is to compress this memory by exploiting inter-layer cache… 5 arXiv — NLP / Computation & Language research 5d ago Which Skill to Distill? SGUID: Selecting a Compact Skill Bank for Model-Skill Co-Evolution arXiv:2610.12367v1 Announce Type: new Abstract: Skills, reusable procedural guidance added at inference, can substantially improve LLM downstream performance (Li et al., 2026). Prior work retrieves skills from a bank by semantic relevance, then uses them as inference-time… 36 arXiv — NLP / Computation & Language research 5d ago Latent Core Tokenizer: Compress, but Meaningfully arXiv:2610.12376v1 Announce Type: new Abstract: Tokenizers are commonly optimized for compression, but a compact vocabulary does not necessarily distribute its capacity evenly across languages. We introduce the Latent Core Tokenizer (LCT), a language-agnostic approach that… 36 arXiv — NLP / Computation & Language research 5d ago Predicting Alignment Generalization with Value Representations arXiv:2610.12410v1 Announce Type: new Abstract: LLM developers post-train their models to exhibit prosocial values and behavioral traits, which are enumerated in an alignment target. However, while recent post-training developments have yielded models that score highly on… 31 arXiv — NLP / Computation & Language research 5d ago An Explainable Header-Centric Framework for Large-Scale Semantic Table Interpretation and Data Quality Assessment arXiv:2610.10541v1 Announce Type: cross Abstract: Knowledge Graph (KG) quality depends not only on downstream graph validation, but also on the quality of tabular metadata used before integration. In metadata-only Semantic Table Interpretation (STI), where cell values are… 25 arXiv — NLP / Computation & Language research 5d ago WorldBench: Evaluating LLMs on Three.js Voxel World Generation arXiv:2610.10622v1 Announce Type: cross Abstract: Large language models can now write complete, interactive 3D worlds as code, but grading those worlds automatically is unreliable. Existing judges take one view of the output: a vision-language model scores a few rendered… 35 arXiv — NLP / Computation & Language research 5d ago Plan-and-Patch: Diffusion Language Models for Agentic Planning arXiv:2610.10786v1 Announce Type: cross Abstract: Planning is increasingly important for long-horizon agents, where successful execution requires coordinating subgoals, tool use, and intermediate outcomes over many steps. Yet assumptions made during planning may be invalidated… 37 arXiv — NLP / Computation & Language research 5d ago NavGPT-3: Harnessing Context in a Hierarchical Navigation Runtime arXiv:2610.10787v1 Announce Type: cross Abstract: Language models trained with long-horizon agentic reinforcement learning can generalize knowledge through reasoning, express precise actions, and pursue goals over many steps, raising the ceiling on what an embodied agent can… 13 arXiv — NLP / Computation & Language research 5d ago Conversational Voice Aesthetic Model with Reinforcement Learning from Human Listeners arXiv:2610.10868v1 Announce Type: cross Abstract: We introduce Conversational Voice Aesthetic Model, a speech large language model for describing the voice aesthetics of real or synthetic speech responses in natural conversational contexts. Given a context and a response speech,… 4 arXiv — NLP / Computation & Language research 5d ago StoreBench: A Live-Commerce Environment for Evaluating and Training Autonomous Operator Agents arXiv:2610.10942v1 Announce Type: cross Abstract: Reinforcement learning environments are now a primary lever for improving large language model (LLM) capabilities in post-training, yet most agentic benchmarks remain static: the world moves only when the agent acts, the reward… 19 arXiv — NLP / Computation & Language research 5d ago GameCommBench: A Unified Benchmark and Type-Aware Evaluation for AI-Generated Game Commentary arXiv:2610.11129v1 Announce Type: cross Abstract: Game commentary is an open-ended generation task requiring multimodal perception, strategic reasoning, and contextual knowledge. Existing AI-Generated Game Commentary (AI-GGC) studies remain fragmented across games, modalities,… 29 arXiv — Machine Learning research 6d ago A Bayesian Mirror Architecture for Emergent Consciousness: Circular Hierarchies, Self-Manifolds, and Hybrid Event-Self Binding arXiv:2610.08792v1 Announce Type: new Abstract: We present a foundational formulation of the Bayesian Mirror Architecture (BMA), a self-referential generative framework in which sensory abstractions, meta-abstractions, and a self-latent interact through circular recursion. The… 33 arXiv — Machine Learning research 6d ago Beyond Baseline Severity: Temporal and Disease-Specific Predictors of Depression Outcomes Following Mindfulness Interventions arXiv:2610.08809v1 Announce Type: new Abstract: Depression severity among patients with chronic or acute medical conditions is influenced by a complex interaction of baseline psychological state, demographic characteristics, clinical context, and engagement with behavioral… 18 arXiv — Machine Learning research 6d ago Transferability and operational reliability of a Prithvi crop classification foundation model under phenological and geographic shift across three continents arXiv:2610.08810v1 Announce Type: new Abstract: Fine-tuned geospatial foundation models (GeoFMs) pretrained on large satellite archives have been shown to improve crop classification accuracy and geographic transferability. However, their operational performance beyond the… 19 arXiv — Machine Learning research 6d ago KVFetch: Temporal Prefetching for the Missing Half of KV Cache Compression arXiv:2610.08811v1 Announce Type: new Abstract: As context windows scale to tens or hundreds of thousands of tokens, KV cache compression has become essential for efficient LLM inference. Existing methods fall into three families: score-based eviction, summary compensation, and… 25 arXiv — Machine Learning research 6d ago Bounded Autonomy and Verifiable Safety for Agentic AI Enabled Automation arXiv:2610.08815v1 Announce Type: new Abstract: Agentic AI-enabled automation cannot be safely deployed in high-stakes environments on probabilistic reasoning alone. A recurring risk is epistemic drift: as reasoning deepens, system behavior may move away from… 20 arXiv — Machine Learning research 6d ago The Cost of Long Memory: State, Context, and Stability Complexity in Sequence Models arXiv:2610.08816v1 Announce Type: new Abstract: Long-range temporal dependence poses a resource question for sequence models: for a specified predictive-memory law, how much state, context, or dynamical criticality is required in order to forecast accurately? We study this… 4 arXiv — Machine Learning research 6d ago DenoFlow: Flow Matching for SSVEP Denoising under Real Physiological Artifacts arXiv:2610.08817v1 Announce Type: new Abstract: Electroencephalography (EEG)-based brain-computer interfaces (BCIs), particularly steady-state visual evoked potential (SSVEP) systems, are highly vulnerable to noise and artifacts, which severely degrade decoding accuracy.… 34 Page 8 of 10 · 500 articles ← Newer Older →
