Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T11:45:22.646912Z
Paper Citation Record · LEDGER
As of 15 August 2026, this Paper Citation Record lists 36 of 36 outbound references and 0 inbound Pith citation observations for arXiv:2607.19794.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-08-01T11:45:22.646912Z
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-15T06:32:42.880941+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links
A source-named dated measurement, never combined with another source.
Source: cited_works
36 of 36 outbound references displayed
External citation measurements
No source-named external measurement is stored.
Observation 70ca29f9-8ae8-45eb-b399-bbb55905f636 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis FinBERT: Financial Sentiment Analysis with Pre-trained Language Models
Reference 1
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Observation 01e51a3f-5023-4962-9cec-0c29cfba5e2c · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis MetaGPT: Meta programming for a multi-agent collaborative framework
Reference 6
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Observation f2d03173-9a73-4548-abd8-edbafb5441b4 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Unresolved cited work
Reference 7
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Observation 3fc53cfd-9dd8-4011-8eec-2b04f2402544 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Mistral 7B
Reference 9
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Observation 0c47ab58-06cb-4b01-afb2-4e7053e04ed9 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Is BERT really robust? a strong baseline for natural language attack on text classifi- cation and entailment
Reference 10
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Observation 27d36794-4f1e-4647-9643-e930ebc51677 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis CAMEL: Commu- nicative agents for “mind” exploration of large language model society
Reference 14
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Observation 04593537-942d-4a86-9d2f-58e369ae6958 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Encouraging di- vergent thinking in large language models through multi- agent debate
Reference 15
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Observation 6f9d17c1-19fa-4f85-b758-bf72681d740f · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis When is a liability not a liability? Textual analysis, dictionaries, and 10-Ks.The Journal of Finance, 66(1):35–65,
Reference 16
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Observation cf78c0fa-d430-48f2-b424-8dc997fd910b · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Gales, Mark J.˙ SelfCheckGPT: Zero-resource black-box hallucination detection for generative large lan- guage models
Reference 18
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Observation fa540caf-f98f-49cc-9d6a-91810feee47e · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis RouteLLM: Learning to Route LLMs with Preference Data
Reference 19
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Observation 87d84281-8ec5-4e45-a960-d341e8765816 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Ignore Previous Prompt: Attack Techniques For Language Models
Reference 20
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Observation 149136f6-3b1e-4889-b7d1-dd360b4df49c · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Sentence-BERT: Sentence embeddings using siamese BERT-networks
Reference 21
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Observation 84c0efd4-eca2-404f-89c6-155c378a4d3b · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Making monolingual sentence embeddings multilingual using knowledge distillation
Reference 22
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Observation 758fc6e8-0a90-4c61-a94f-d33a8229bb13 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Active learning literature sur- vey
Reference 23
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Observation b2185f6a-6193-4e56-8097-3c6db81b66ac · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Qwen2.5 Technical Report
Reference 25
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Observation 24dd6e5b-073f-4729-ab43-f2ab3c4cf95a · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis https://huggingface.co/datasets/zeroshot/ twitter-financial-news-sentiment,
Reference 26
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Observation a5206f43-21e1-489b-85ea-074ca8a1fb7c · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Mixture of cheap and expensive models for cost-effective inference
Reference 27
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Observation a7eee2d7-adec-4f52-ae3d-707a676347ee · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Self- consistency improves chain of thought reasoning in language models
Reference 28
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Observation 37cc9a4f-829a-44e6-b42f-059b4f8712c9 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis HuggingFace’s transformers: State-of-the-art natural language process- ing
Reference 29
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Observation 5bf25539-f83a-46c4-be87-9897c77a0250 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis BloombergGPT: A Large Language Model for Finance
Reference 30
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Observation 76b7f7bb-38bb-4136-bc4f-52ce7408c206 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis AutoGen: En- abling next-gen LLM applications via multi-agent conver- sation framework
Reference 31
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Observation 322ed4f2-4daf-4d64-9959-dabfbccc9175 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis PIXIU: A large language model, instruction data and evaluation bench- mark for finance
Reference 32
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Observation fac9ac24-bb7c-4e46-a810-121e10ca9c05 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis FinBERT-tone- Chinese: Domain-specific BERT for chinese finan- cial sentiment
Reference 33
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Observation 9d211644-a29c-44fc-87b2-d899f829e179 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis FinBERT: A Pretrained Language Model for Financial Communications
Reference 34
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Observation fbe51f29-764b-4bd7-8d89-57c1722d5bbc · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis FinGPT: Open-source financial large language models
Reference 35
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Observation fe1f52d2-da68-421e-8e70-1080c1168523 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Judging LLM-as-a-Judge with MT-Bench and Chatbot Arena
Reference 36
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Observation de173938-26a7-4d79-ba08-1aff4cdf4cfc · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Large Language Model Routing with Benchmark Datasets
Reference 2009
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Observation 53e9f6fd-117d-440b-a24e-3020364efc41 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Good debt or bad debt: Detecting semantic orientations in economic texts
Reference 2011
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Observation 9f7406e5-1b26-484f-ab92-8f89a06f18cc · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Survey of hallucination in natural language generation.ACM Computing Surveys, 55(12):1–38,
Reference 2014
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Observation f10b9fdc-4c41-4f26-9d81-b7b9f8565c0a · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis A Survey of Large Language Models in Finance (FinLLMs)
Reference 2017
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Observation f1d25316-1c12-4387-b586-fa0c8a1b072f · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis FrugalGPT: How to Use Large Language Models While Reducing Cost and Improving Performance
Reference 2019
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Observation 78781b94-db38-4a6f-a671-e3777eff2d5e · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Billion-scale similarity search with GPUs
Reference 2020
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Observation b65ff8b5-626c-4dd1-a187-3d7156b33f19 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Simple and scal- able predictive uncertainty estimation using deep ensem- bles
Reference 2021
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Observation 30688598-213e-4ead-94e7-2e0f6da8d20f · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis Tenenbaum, and Igor Mordatch
Reference 2022
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Observation ee79a955-1a92-475a-a1a2-2323aa0f0306 · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis LLM.int8(): 8-bit matrix multiplication for transformers at scale
Reference 2023
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Observation 832b219b-92cf-4c85-9544-900e57e7cfde · outbound
TriAgent: Divergence-Aware Multi-Agent Committees for Cost-Efficient Financial Sentiment Analysis https://huggingface.co/datasets/ChanceFocus/ flare-fpb,
Reference 2024
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No inbound Pith citation observations are available.