News / #paper Tag Research papers 500 articles archived under #paper · RSS Sign in to follow arXiv — NLP / Computation & Language research 2d ago Sycophancy Suppression Can Impair Rational Updating: Anti-Sycophancy Should Preserve the Ability to Update arXiv:2608.26511v1 Announce Type: new Abstract: Large language models often exhibit sycophancy, revising their answers to align with users when users push back. Such answer flips, however, can arise from different causes. One possibility is that the model simply aligns with the… 30 arXiv — NLP / Computation & Language research 2d ago Multi-Expert Conformal Risk Control for Pairwise LLM Judging in Open-Ended Dialogue arXiv:2608.26529v1 Announce Type: new Abstract: In this paper, we explore multi-expert Conformal Risk Control (CRC) algorithms for pairwise LLM-as-a-Judge evaluation in open-ended dialogue. Our core insight is that multi-expert aggregation offers a complementary remedy to CRC:… 11 arXiv — NLP / Computation & Language research 2d ago SPEAR: Distilling Domain-Adaptive Reasoning Skeletons via Sequential Symbolic Alignment in Reinforcement Learning arXiv:2608.26550v1 Announce Type: new Abstract: Reinforcement learning-based knowledge distillation has the potential to transfer complex reasoning from teacher to student models, yet it currently faces a critical dilemma: researchers must choose between sparse outcome-based… 34 arXiv — NLP / Computation & Language research 2d ago SPT: Skills as Pre-Training Data for Agentic Language Models arXiv:2608.26563v1 Announce Type: new Abstract: Agentic (tool-using) language models are mainly trained on tool-call traces and agent trajectories during post-training. These data provide direct behavioral supervision, but producing them requires task environments, execution,… 13 arXiv — NLP / Computation & Language research 2d ago Dependency-Aware Revocable Decoding for Efficient Diffusion Large Language Model Inference arXiv:2608.26574v1 Announce Type: new Abstract: Diffusion large language models (dLLMs) offer a promising alternative to autoregressive generation by decoding multiple tokens in parallel through iterative denoising. However, increasing decoding parallelism often degrades… 29 arXiv — NLP / Computation & Language research 2d ago Double Trouble: Bilingual Pretraining Leaves Language-Conditioned Effects in Shared-Language Representations arXiv:2608.26576v1 Announce Type: new Abstract: When researchers compare multilingual models for probing, interpretability, or cross-lingual transfer, they often align embedding spaces and assume that shared-language representations are comparable. We show that this assumption… 13 arXiv — NLP / Computation & Language research 2d ago Surgical Alignment in Knowledge Graph Training for Clinical Diagnosis with Large Language Models arXiv:2608.26587v1 Announce Type: new Abstract: Biomedical knowledge graphs (KGs) offer structured medical knowledge that can ground large language model (LLM) reasoning in clinical diagnosis application, yet how KG signal should be integrated into LLMs remains an open question.… 8 arXiv — NLP / Computation & Language research 2d ago Benchmarking Clinical Decision Pathway Adherence in Large Language Models arXiv:2608.26592v1 Announce Type: new Abstract: Following clinical decision pathways (CDPs) defined by clinical practice guidelines is essential for safe and reliable medical decision-making. However, existing medical large language model (LLM) benchmarks mainly evaluate… 4 arXiv — NLP / Computation & Language research 2d ago Not Just Reason, Not Just Scan: Reinforcement Learning for Proactive Scientific Error Verification over Academic Paper arXiv:2608.26596v1 Announce Type: new Abstract: Multimodal large language models (MLLMs) are increasingly capable scientific assistants, yet they remain far from fully autonomous research. This transition requires models to actively inspect academic papers, build global evidence… 4 arXiv — NLP / Computation & Language research 2d ago Which Metrics Save the Most Human Annotation? Prediction-Powered Evaluation and Meta-Evaluation arXiv:2608.26638v1 Announce Type: new Abstract: Across various non-verifiable tasks, human evaluation is reliable but expensive, while automatic metrics are more scalable but often biased. Building on prediction-powered inference (PPI), we propose prediction-powered evaluation,… 35 arXiv — NLP / Computation & Language research 2d ago Information-Guided Frontier Decoding: Contextual Utility-Driven Commitment in dMLLMs arXiv:2608.26641v1 Announce Type: new Abstract: Decoding quality in diffusion multimodal language models (dMLLMs) depends heavily on the order in which masked tokens are committed. Existing confidence-based strategies prioritize locally easy tokens, but confidence does not… 19 arXiv — NLP / Computation & Language research 2d ago Meta-Learning Where to Allocate Experts: Task-Conditioned Layer-Wise Compression for MoEs arXiv:2608.26650v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models route each token to a subset of expert networks, increasing capacity while keeping per-token computation sparse. In many deployed MoEs, the number of active experts is fixed across layers and tasks,… 16 arXiv — NLP / Computation & Language research 2d ago Do LLMs Understand Personality? Rethinking Persona Fidelity Evaluation through Structured Behavioral Inference arXiv:2608.26674v1 Announce Type: new Abstract: As large language models are increasingly deployed to simulate diverse human characters, ensuring persona fidelity, defined as the extent to which an agent's behavior consistently reflects the psychological and stylistic… 6 arXiv — NLP / Computation & Language research 2d ago FOCUS & RePAIR: Mitigating Text Degeneration via Token-Level Guidance for Pruned Large Language Models arXiv:2608.26676v1 Announce Type: new Abstract: Pruning is a practical approach to compress large language models (LLMs), but it can amplify text degeneration, especially repetition loops, even when perplexity and task accuracy remain largely unchanged. In this work, we present… 31 arXiv — NLP / Computation & Language research 2d ago Beyond Reflection: Affirmation as a Promising Behavioral Marker Associated with Quality in Text-Based Counseling arXiv:2608.26689v1 Announce Type: new Abstract: While AI-assisted text-based counseling is gaining attention, it remains empirically unclear which counselor behaviors are associated with higher dialogue quality. Existing research often focuses heavily on Reflection, borrowing… 32 arXiv — NLP / Computation & Language research 2d ago Scaling phoneme-based TTS augmentation for ASR: A unified pipeline and controlled study arXiv:2608.26697v1 Announce Type: new Abstract: Synthetic speech provides scalable supervision for automatic speech recognition (ASR), but its benefit depends on the selected texts, reference speech, and amount of synthesized data. We present a unified phoneme-based TTS-to-ASR… 14 arXiv — NLP / Computation & Language research 2d ago PragAlign: Evidence-Sensitive Reply Assistance Across Chinese and Japanese Appropriateness Judgments arXiv:2608.26700v1 Announce Type: new Abstract: Reply assistance in multilingual settings requires linguistic competence and culturally situated judgments of appropriateness. We present PragAlign, which separates context reading from selective clarification, and evaluate it… 23 arXiv — NLP / Computation & Language research 2d ago Towards Expert Financial QA via Self-Improving RAG arXiv:2608.26706v1 Announce Type: new Abstract: Expert-level financial question answering requires both grounded verification to catch numeric hallucinations and audit trails for regulatory compliance, attributes that standard single-pass RAG systems lack. We take a step toward… 6 arXiv — NLP / Computation & Language research 2d ago Preserving General Capabilities during Domain Specialization with Uncertainty-Calibrated MOPD arXiv:2608.26735v1 Announce Type: new Abstract: Specializing large language models to vertical domains improves domain-specific behavior but often degrades general capabilities such as reasoning, coding, instruction following, and creative writing. We study this domain--general… 29 arXiv — NLP / Computation & Language research 2d ago Letters hide the truth from our eyes: English homophones have meaningfully different phonetic realizations arXiv:2608.26749v1 Announce Type: new Abstract: The distribution of spoken word duration of English homophones is known to co-vary with frequency of use. This study investigates whether other aspects of the phonetic realization of homophones also differ. A series of quantitative… 26 arXiv — NLP / Computation & Language research 2d ago Equal Ranking Quality, Different Decisions: Training Order-Consistent LLM Scorers arXiv:2608.26762v1 Announce Type: new Abstract: Rerankers, reward models and multi-document QA scorers score candidate documents or responses in one LLM prompt, so each score depends on their order. Such scorers are selected on ranking quality, but their scores determine a… 27 arXiv — NLP / Computation & Language research 2d ago Instruction Quality Matters: Refining Instructions for Effective Preference Learning arXiv:2608.26779v1 Announce Type: new Abstract: Preference learning optimizes models using response pairs, yet the informativeness of these pairs is fundamentally shaped by the instructions from which they are generated. We identify instruction quality as a hidden bottleneck in… 25 arXiv — NLP / Computation & Language research 2d ago Behavior2Trip: Towards Personalized Travel Planning via User Behavior Trajectory arXiv:2608.26807v1 Announce Type: new Abstract: Travel planning agents assist users in generating personalized travel plans by modeling their individual preferences. Existing agents either rely on explicit user instructions or engage in multi-turn clarification to elicit user… 7 arXiv — NLP / Computation & Language research 2d ago RuleWeaver: Benchmarking Rule-Centered Scenario Reasoning for Large Language Models arXiv:2608.26832v1 Announce Type: new Abstract: Large language models (LLMs) are increasingly applied to specialized domains, where effective use of domain expertise often requires reasoning over complex rules in concrete scenarios. However, existing benchmarks only partially… 5 arXiv — NLP / Computation & Language research 2d ago Evaluating Confidence-Gated Retrieval with Matched Trajectory Replay arXiv:2608.26846v1 Announce Type: new Abstract: Interactive language-model agents use confidence signals to decide whether to answer immediately, retrieve additional evidence (from memory or external knowledge), or defer. Yet confidence is usually evaluated in isolation, without… 13 arXiv — NLP / Computation & Language research 2d ago Planting a Latent Variable in Natural-Looking Text: a More Realistic Test of Belief States in LLMs and Their Link to Concept Geometry arXiv:2608.26887v1 Announce Type: new Abstract: LLMs are thought to track "belief states," i.e., running probability distributions over the latent variables that govern language (Shai et al., 2024; Sarfati et al., 2026), but so far this has only been comprehensively demonstrated… 6 arXiv — NLP / Computation & Language research 2d ago TabuLM: Morphology-Aware Tabular Pre-training for Low-Resource Languages arXiv:2608.26923v1 Announce Type: new Abstract: We present TabuLM, the first language model pre-trained on Kinyarwanda tabular data. Kinyarwanda is a morphologically rich Bantu language spoken by over 12 million people in Rwanda, yet lacks any dedicated tabular representation… 25 arXiv — NLP / Computation & Language research 2d ago Mapping Written Words to Spoken Words in a Different Language Using Only Visual Grounding arXiv:2608.26925v1 Announce Type: new Abstract: In many low-resource settings, even just eliciting speech for data collection is difficult. One promising approach has been to ask speakers to describe images. But how do we build models from such visually grounded speech data?… 12 arXiv — NLP / Computation & Language research 2d ago KinyaEmbed: Contrastive Sentence Embeddings for Kinyarwanda via Multi-Stage Curriculum Training arXiv:2608.26941v1 Announce Type: new Abstract: We present KinyaEmbed, the first dedicated sentence embedding model for Kinyarwanda, a morphologically rich Bantu language spoken by over 12 million people in Rwanda. Existing multilingual embedding models such as LaBSE, mE5-large,… 34 arXiv — NLP / Computation & Language research 2d ago Squeezing More from Limited Data with Recursive Transformers arXiv:2608.26973v1 Announce Type: new Abstract: Pre-training under limited data requires a different view of scaling than web-scale language modeling. With a fixed data budget but relatively abundant compute, increasing parameter count helps only up to an optimal scale; beyond… 27 arXiv — NLP / Computation & Language research 2d ago JudgeStealer: Extracting LLM Judging Capabilities across Evaluation Protocols arXiv:2608.26982v1 Announce Type: new Abstract: Large language model (LLM) judges are increasingly used across various evaluation scenarios, making their judgment capabilities valuable intellectual property. However, black-box access exposes these capabilities to model… 34 arXiv — NLP / Computation & Language research 2d ago ITL: Interpretable Document Alignment with Structured Reference Frameworks arXiv:2608.27031v1 Announce Type: new Abstract: Measuring alignment between documents and structured reference frameworks requires identifying conceptual evidence distributed throughout the text and reporting it through measures that are quantitative, interpretable, and… 19 arXiv — NLP / Computation & Language research 2d ago Representing and Parsing Korean Constituency Structure at Different Levels of Granularity arXiv:2608.27035v1 Announce Type: new Abstract: Korean constituency parsing raises a representational challenge because the terminal units of a phrase-structure tree do not straightforwardly correspond to simple surface words. Korean eojeols are morphologically complex spacing… 7 arXiv — NLP / Computation & Language research 2d ago Reasoning about In-Context Samples for Machine-Translation arXiv:2608.27036v1 Announce Type: new Abstract: Large Language Models (LLMs) can be trained to perform chain-of-thoughts reasoning in order to improve the reliability of their responses. In this work, we investigate how explicit reasoning can be leveraged for LLM-Based Machine… 18 arXiv — NLP / Computation & Language research 2d ago Cascaded Batch Prompting arXiv:2608.27038v1 Announce Type: new Abstract: Although batch prompting makes large language model inference more efficient by processing multiple instances simultaneously, it suffers from unpredictable downstream task performance. We propose cascaded batch prompting, a… 37 arXiv — NLP / Computation & Language research 2d ago Research Design Tracking and Assessment for the Social Sciences arXiv:2608.27049v1 Announce Type: new Abstract: Reliable assessment of causal research designs in the social sciences is critical for evidence-based policy-making, yet has so far relied entirely on manual expert analysis. We introduce Automated Research Design Tracking and… 32 arXiv — NLP / Computation & Language research 2d ago DocTalkBN: A Novel Dataset of Expert Telemedicine Conversations in Bengali arXiv:2608.27110v1 Announce Type: new Abstract: Reliable medical conversational AI requires authentic expert--patient interaction data, yet such datasets remain scarce, especially for low-resource languages such as Bengali. We present DocTalkBN, a large-scale multimodal dataset… 13 arXiv — NLP / Computation & Language research 2d ago Cross-Lingual Alignment Without Joint Training: Do Monolingual Language Models Converge on Universal Representations? arXiv:2608.27115v1 Announce Type: new Abstract: Cross-lingual alignment in multilingual language models is typically attributed to joint training: shared parameters, mixed-language batches, or explicit alignment objectives. We ask whether monolingual models trained on… 8 arXiv — NLP / Computation & Language research 2d ago TwinKV: A Composable Repair Pass for KV Cache Eviction via Pairwise Key Redundancy arXiv:2608.27128v1 Announce Type: new Abstract: Long-context inference is bottlenecked by the memory footprint of the key-value (KV) cache, especially for small models under tight resource budgets. Existing KV cache eviction methods score tokens using the model's attention… 14 arXiv — NLP / Computation & Language research 2d ago Said Aloud, Read Different: Cross-Modal Instability in Multimodal Models arXiv:2608.27135v1 Announce Type: new Abstract: Multimodal foundation models are increasingly used in speech-first assistants that must interpret spoken queries and produce visually grounded decisions. Yet it remains unclear whether semantically equivalent queries yield… 32 arXiv — NLP / Computation & Language research 2d ago STAR : Sentence Translation Alignment Rate for Document-to-Document Machine Translation arXiv:2608.27161v1 Announce Type: new Abstract: Large Language Models (LLMs) have enabled a shift from sentence-level to document-to-document (Doc2Doc) machine translation, promising improved global coherence. However, document-to-document generation in a single pass frequently… 11 arXiv — NLP / Computation & Language research 2d ago Prediction of Prediction (PoP): Inter-Layer Activation Fusion for Single-Pass Hallucination Detection in Large Language Models arXiv:2608.27165v1 Announce Type: new Abstract: Autoregressive large language models (LLMs) routinely generate factually incorrect outputs with high decoding confidence, limiting their deployment in high-stakes workflows. Existing output-stage uncertainty metrics can fail when… 8 arXiv — NLP / Computation & Language research 2d ago When Text Misleads: Inconsistent-Aware Reasoning for Audio-Grounded Dialogue arXiv:2608.27176v1 Announce Type: new Abstract: Understanding spoken dialogue requires joint reasoning over lexical content and paralinguistic acoustic signals such as emotion and conversational intent. However, existing evaluations often allow shortcuts based on transcripts or… 32 Hugging Face Daily Papers research 3d ago LibriBrain100: One Hundred Hours of Broad and Deep MEG Data for Neural Speech Decoding at Scale Abstract LibriBrain100 is a large-scale MEG speech dataset that demonstrates improved decoding through extensive within-subject recordings and multi-subject supervised fine-tuning of pre-trained models. Generated by thinkingmachines/Inkling-Small We introduce LibriBrain100, a… 12 arXiv — Machine Learning research 3d ago Dynamic Influence-Weighted Distillation for Single-IMU Activity Recognition arXiv:2608.24904v1 Announce Type: new Abstract: Inertial sensors at multiple body locations can improve activity recognition, but requiring every sensor at inference increases the deployment burden. We study whether four synchronized IMUs available during training can improve a… 37 arXiv — NLP / Computation & Language research 3d ago GreenLeaf Law Embed Tiny: A Compact Embedding Model for Legal Domain Retrieval arXiv:2608.24936v1 Announce Type: cross Abstract: We present GreenLeaf Law Embed Tiny, a 0.6B parameter embedding model for legal domain retrieval. GreenLeaf-Tiny achieves 75.11% on the Massive Legal Embedding Benchmark (MLEB) and 64.38% on MTEB(Law, v1),demonstrating… 14 arXiv — Machine Learning research 3d ago Multi-Modal Anomaly Detection: A Survey arXiv:2608.24937v1 Announce Type: new Abstract: Multi-Modal Anomaly Detection (MMAD) detects rare abnormal events from heterogeneous data sources and is increasingly used in safety- and reliability-critical applications such as industrial inspection and cybersecurity. Yet the… 9 arXiv — Machine Learning research 3d ago ExFold: Unified Expert Folding for Training-Free MoE Prefill-Decode Acceleration arXiv:2608.24938v1 Announce Type: new Abstract: Mixture-of-Experts (MoE) models scale capacity for strong quality while keeping per-token compute bounded through sparse expert activation. Yet low-latency MoE serving is increasingly challenging, because it spans two inference… 9 arXiv — Machine Learning research 3d ago When Does Frequency Decomposition Benefit Physics-Informed Neural Networks? A Preliminary Ablation Study arXiv:2608.24940v1 Announce Type: new Abstract: Partial differential equations (PDEs) often have high-frequency and multi-scale features that neural networks struggle to approximate. Physics-Informed Neural Networks (PINNs) build the governing equations directly into training,… 16 arXiv — Machine Learning research 3d ago FAMPWQ: Fisher Information-based Adaptive Mixed Precision Weight Quantization for Effective LLM Inference arXiv:2608.24945v1 Announce Type: new Abstract: Recent years have witnessed remarkable achievements of Large Language Models (LLMs) in multiple domains, while the excessive resource requirements of LLMs hinder the deployment on resource-constrained devices. Although model… 9 Page 4 of 10 · 500 articles ← Newer Older →
