Natural language processing

Classical and neural NLP: translation, question answering, tokenization and the evaluation of language understanding.

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arXiv Machine Learning

Jul 7

SalAngaBhava: A Sinhala Market Dataset for Aspect-based Sentiment Analysis

arXiv:2607. 05259v1 Announce Type: cross Abstract: Sentiment analysis has been a primary domain under Natural Language Processing (NLP) from its inception as it plays a vital role in both real-world and research applications.

By Lakshani Galwatta, Nisansa de Silva, Sarangi Aththanayake, Adithya Galwatta

nlp benchmarks

arXiv Machine Learning

Jul 7

Coverage-Controlled Preference Mining from Noisy Claim Verification for Evidence-Grounded Generation

arXiv:2603. 10494v2 Announce Type: replace-cross Abstract: Evidence-grounded generation produces summaries whose claims should be supported by supplied evidence, but claim-level verifiers provide noisy feedback and can reward models that simply say less.

By Weixin Liu, Congning Ni, Qingyuan Song, Susannah L. Rose, Murat Kantarcioglu, Bradley A. Malin, Zhijun Yin

llms rag nlp reinforcement-learning

arXiv AI

Jul 7

Speaker-Disentangled Chunk-Wise Regression for Syllabic Tokenization

arXiv:2607. 04064v1 Announce Type: cross Abstract: Unsupervised syllabic tokenization aims to learn discrete syllabic tokens that capture latent linguistic content-related structure from raw speech.

By Ryota Komatsu, Kota Kawakita, Takuma Okamoto, Takahiro Shinozaki

llms nlp efficiency benchmarks

arXiv AI

Jul 7

Walrus: A Cross-Domain Foundation Model for Continuum Dynamics

arXiv:2511. 15684v2 Announce Type: replace-cross Abstract: Foundation models have transformed machine learning for language and vision, but achieving comparable impact in physical simulation remains a challenge.

By Michael McCabe, Payel Mukhopadhyay, Tanya Marwah, Bruno Regaldo-Saint Blancard, Francois Rozet, Cristiana Diaconu, Lucas Meyer, Kaze W. K. Wong, Hadi Sotoudeh, Alberto Bietti, Irina Espejo, Rio Fear, Siavash Golkar, Tom Hehir, Keiya Hirashima, Geraud Krawezik, Francois Lanusse, Rudy Morel, Ruben Ohana, Liam Parker, Mariel Pettee, Jeff Shen, Kyunghyun Cho, Miles Cranmer, Shirley Ho

llms nlp efficiency benchmarks

arXiv AI

Jul 7

SeeMe: Mitigating Hallucinations in Large Vision-Language Models through Effective Visual Token Engineering

arXiv:2607. 04163v1 Announce Type: cross Abstract: Large Vision-Language Models (LVLMs) have achieved remarkable progress in visual understanding tasks such as image captioning and visual question answering.

By Kai Tang, Jinhao You, Bohua Zhang, Yichen Guo, Yiding Sun, Dongxu Zhang, Chenxi Li, Xiande Huang, Shanghang Zhang

llms nlp multimodal benchmarks safety

arXiv AI

Jul 7

EventCoT: Event-centric Video Chain-of-thought for Reasoning Temporal Localization

arXiv:2607. 04872v1 Announce Type: cross Abstract: Reasoning temporal localization (RTL) requires a model to generate an answer that itself contains the time interval supporting it, so high-level reasoning and precise temporal grounding must be produced jointly in a single response.

By Youngkil Song, Yoonjae Baek, Dongwon Kim, Inho Kim, Dongkeun Kim, Suha Kwak

rag nlp benchmarks

arXiv AI

Jul 7

IRC-Bench: Recognizing Entities from Contextual Cues in First-Person Reminiscences

arXiv:2605. 06142v2 Announce Type: replace-cross Abstract: When people recount personal memories, they often refer to people, places, and events indirectly, relying on con-textual cues rather than explicit names.

By Yehudit Aperstein, Eden Moran, Alexander Apartsin

llms rag nlp fine-tuning benchmarks

arXiv Machine Learning

Jul 7

Incentivizing Vision Language Models to Search for Long Video Question Answering

arXiv:2607. 02959v1 Announce Type: cross Abstract: We introduce VSeek, an agentic framework that transforms long-video question answering (LVQA) from a passive, single-pass perception task into a multi-turn retrieval process.

By Harsh Goel, S P Sharan, Sahil Shah, Minkyu Choi, Joungbin An, Kristen Grauman, Sandeep P. Chinchali

llms agents nlp reinforcement-learning benchmarks

arXiv AI

Jul 7

When Simpler Is Better: Evaluating Translation Pipelines for Medieval Latin Manuscripts

arXiv:2607. 03836v1 Announce Type: cross Abstract: Despite remarkable progress in machine translation, Vision Language Models (VLMs) struggle on historical manuscripts, a domain that stresses core Natural Language Processing (NLP) capabilities: low-resource transliteration, archaic vocabulary, and noisy input signals.

By Nguyen Kim Hai Bui, Md. Easin Arafat, Tam\'as G\'abor Orosz, Mufti Mahmud

llms rag computer-vision nlp multimodal benchmarks

arXiv AI

Jul 7

Interactive Learning for LLM Reasoning

arXiv:2509. 26306v5 Announce Type: replace Abstract: Existing multi-agent learning approaches have developed interactive training environments to explicitly promote collaboration among multiple Large Language Models (LLMs), thereby constructing stronger multi-agent systems (MAS).

By Hehai Lin, Shilei Cao, Sudong Wang, Haotian Wu, Minzhi Li, Linyi Yang, Juepeng Zheng, Chengwei Qin

llms agents nlp benchmarks

arXiv AI

Jul 7

Detecting Hallucinations in Retrieval-Augmented Generation through Grounding-Aware Sensitivity by Perturbation (GASP)

arXiv:2607. 04223v1 Announce Type: cross Abstract: Retrieval-augmented generation (RAG) reduces but does not eliminate hallucination, and existing detectors return a single answer-level score that does not indicate which sentence is unsupported, or why.

By Mohamed Aly Bouke

rag nlp benchmarks safety

arXiv Machine Learning

Jul 7

MANCE: Manifold Aware Concept Erasure

arXiv:2607. 03973v1 Announce Type: new Abstract: Concept erasure aims to remove a target concept from a representation while preserving the other information encoded in it.

By Matan Avitan, Yoav Goldberg, Yanai Elazar

llms nlp benchmarks

arXiv AI

Jul 7

Evaluating LLM-Based Regression Test Generation

arXiv:2501. 11086v2 Announce Type: replace-cross Abstract: Large Language Models (LLMs) have shown tremendous promise in automated software engineering.

By Jing Liu, Seongmin Lee, Eleonora Losiouk, Marcel B\"ohme

llms nlp benchmarks

arXiv AI

Jul 7

HiFA4: Training-Free 4-bit FlashAttention on Ascend HIF4 NPUs for LLM Inference

arXiv:2607. 04302v1 Announce Type: cross Abstract: We present HiFA4, a post-training operator-level design that executes both QK^T and PV in FlashAttention as 4-bit HIF4 Cube GEMMs for LLM inference on Ascend NPUs, while maintaining the online softmax state in FP16.

By Hui Dong, Yanzhao Li, Jie Gao, Chunlu Li, Zhiyuan Zhang, Yupeng Sun, Zhenyuan Chen, Zhiqiang Zou

llms nlp efficiency benchmarks

arXiv AI

Jul 7

EyeMulator: Improving Code Language Models by Mimicking Human Visual Attention

arXiv:2508. 16771v3 Announce Type: replace-cross Abstract: Code Language Models (CodeLLMs) learn token importance from data correlations, whereas human developers attend selectively to semantically salient code.

By Yifan Zhang, Chen Huang, Yueke Zhang, Jiahao Zhang, Toby Jia-Jun Li, Collin McMillan, Kevin Leach, Yu Huang

llms nlp fine-tuning benchmarks

arXiv AI

Jul 7

STELLA: Efficient Sensor-to-LLM Translation for On-Device Human Activity Recognition

arXiv:2607. 03089v1 Announce Type: cross Abstract: HAR is increasingly expected to run continuously on edge devices, yet recent LLM-based methods remain hard to deploy: raw sensor prompts are long, cloud inference adds latency and privacy risk, and fine-tuned LLM pipelines turn general-purpose models into task-specific classifiers.

By Nirhoshan Sivaroopan, Albert Zomaya, Kanchana Thilakarathna

llms rag nlp fine-tuning benchmarks safety

arXiv AI

Jul 7

Automating the Design of Embodied Agent Architectures

arXiv:2606. 30111v2 Announce Type: replace-cross Abstract: Embodied agents are typically built as hand-designed compositions of perception, memory, planning, and action modules.

By Jian Zhou, Sihao Lin, Jin Li, Shuai Fu, Gengze Zhou, Qi Wu

agents nlp robotics efficiency multimodal

arXiv AI

Jul 7

Parity-Aware Byte-Pair Encoding: Improving Cross-lingual Fairness in Tokenization

arXiv:2508. 04796v3 Announce Type: replace-cross Abstract: Tokenization is the first -- and often least scrutinized -- step of most NLP pipelines.

By Negar Foroutan, Clara Meister, Debjit Paul, Joel Niklaus, Sina Ahmadi, Antoine Bosselut, Rico Sennrich

nlp safety

arXiv AI

Jul 7

DrugAgent: Reliable Multi-Agent Integration of Conflicting Biomedical Evidence for Drug-Target Interaction Assessment

arXiv:2408. 13378v5 Announce Type: replace Abstract: Workflows in drug-target interaction (DTI) assessment require integrating heterogeneous data from predictive models, curated resources, and observations from experimental literature.

By Yoshitaka Inoue, Tianci Song, Xinling Wang, Rui Kuang, Tianfan Fu, Augustin Luna

llms rag agents nlp benchmarks

arXiv AI

Jul 7

Parameter Efficient Multimodal Instruction Tuning for Romanian Vision Language Models

arXiv:2512. 14926v2 Announce Type: replace-cross Abstract: Focusing on low-resource languages is an essential step toward democratizing generative AI.

By George-Andrei Dima, R\u{a}zvan-Alexandru Sm\u{a}du, Dumitru-Clementin Cercel

llms nlp fine-tuning multimodal